presentation on self introduction

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How to Introduce Yourself in a Presentation [with Examples]

In this post, we are going to cover the best way, a very simple three-step process that will help you introduce yourself in a presentation. A summary of the steps is below.

• Start with your name and company (or organization or school).
• Tell your audience what problem you can solve for them.
• Share some type of proof (social proof works best) that you can solve this problem.

I will break down each step into a simple-to-follow process. But first… a little background.

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First, Identify What Your Audience Wants from Your Presentation

So, before you design your introduction, think about what your audience wants from your presentation. Why do they want to spend their valuable time listening to you? Are going to waste their time? Or, are you going to provide them with something valuable?

For instance, I have expertise in a number of different areas. I’m a public speaking coach, a keynote speaker, a best-selling author, a search engine optimization specialist, and a popular podcaster. However, if I delivered that sentence to any audience, the most likely reaction would be, “So what?” That sentence doesn’t answer any of the above questions. The statement is also really “me-focused” not “audience-focused.”

So, when I start to design my self-introduction, I want to focus just on the area of expertise related to my topic. I’m then going to answer the questions above about that particular topic. Once you have these answers, set them aside for a second. They will be important later.

How to Introduce Yourself in a Presentation in Class.

Instead, you probably want to add in a fun way to start a speech . For example, instead of introducing yourself in your class speech and starting in an awkward way, start with a startling statistic. Or start with a summary of your conclusion. Or, you could start the presentation with an inspirational quote.

Each of these presentation starters will help you lower your nervousness and decrease your awkwardness.

If you are delivering a speech in a speech competition or to an audience who doesn’t know you try this technique. Just introduce yourself by saying your name , the school you represent , and your topic . Make it easy. This way you get to your content more quickly and lower your nervousness.

Typically, after you get the first few sentences out of the way, your nervousness will drop dramatically. Since your name, school, and topic should be very easy to remember, this takes the pressure off you during the most nervous moments.

Obviously, follow the guidelines that your teacher or coach gives you. (The competition may have specific ways they want you to introduce yourself.)

How to Introduce Yourself in a Business Presentation — A Step-by-Step Guide.

In a professional setting, when new people walk into a meeting and don’t know what to expect, they will feel uncomfortable. The easiest way to ease some of that tension is to chat with your audience as they come into the room.

By the way, if you are looking for a template for an Elevator Speech , make sure to click this link.

Step #1: Start with your name and company name (or organization).

This one is easy. Just tell your audience your name and the organization that you are representing. If your organization is not a well-known brand name, you might add a short clarifying description. For instance, most people outside of the training industry have never heard of The Leader’s Institute ®. So, my step #1 might sound something like…

Hi, I’m Doug Staneart with The Leader’s Institute ®, an international leadership development company…

Still short and sweet, but a little more clear to someone who has never heard of my company.

Should you give your job title? Well… Maybe and sometimes. Add your title into the introduction only if your title adds to your credibility.

For example, if you are delivering a financial presentation and you are the Chief Financial Officer (CFO) of your company, you might mention that. Your title adds to your credibility. However, if the CFO is delivering a presentation about the value of joining a trade association, the CFO title adds little credibility. So, there is very little value in adding the title.

Step #2: Tell your audience what problem you can solve for them.

For instance, if my topic is how to deliver presentations, I have to determine why the audience would care. What problem will they have that I can help them with? For my audiences, the problem that I most often help people with is how to eliminate public speaking fear. Once I have the problem, I add that to my introduction by using the words, “I help people…”

Hi, I’m Doug Staneart with The Leader’s Institute ®, an international leadership development company, and I help people eliminate public speaking fear.

However, if my topic is How to Close a Higher Percentage of Sales Presentations , I’d likely want to alter my introduction a little. I might say something like…

Hi, I’m Doug Staneart with The Leader’s Institute ®, an international leadership development company, and I help people design more persuasive sales presentations.

I have expertise in both areas. However, I focus my introduction on just the expertise that is applicable to this audience. If I gave the first introduction to the second audience, they will likely respond by thinking, well, I don’t really get nervous speaking, so I guess I can tune out of this speech .

So, create a problem statement starting with, “I help people…” Make the statement apply to what your audience really wants.

Step #3: Share some type of proof (social proof works best) that you can solve this problem.

By the way, if you just do steps #1 and #2, your introduction will be better than most that you will hear. However, if you add Step #3, you will gain more respect (and attention) from your audience. Without adding some type of proof that you can solve this problem, you are just giving your opinion that you are an expert. However, if you can prove it, you are also proving that you are an expert.

This is the tricky part. For some reason, most people who get to this part feel like they haven’t accomplished great things, so they diminish the great accomplishments that they do have.

For instance, an easy way to offer proof is with a personal story of how you have solved that problem in the past.

A Few Examples of How to Introduce Yourself Before a Presentation.

For instance, one of my early clients was a young accountant. When I was working with him, he came up with the following introduction, “I’m Gary Gorman with Gorman and Associates CPA’s, and I help small businesses avoid IRS audits.” It was a great, audience-focused attention-getter. (No one wants to get audited.) However, as an accountant, it wasn’t like his company was getting a lot of five-star reviews on Yelp! So, he was kind of struggling with his social proof. So, I asked him a series of questions.

Me, “How many clients do you have?”

Gary, “Over 300.”

Me, “How many small business tax returns have you processed?”

Gary, “Well, at least a couple hundred a year for 15 years.”

Me, “So, at least 3000?” He nodded. “How many of your 300 clients have been audited since you have been representing them?”

He looked at me and said, “Well, none.”

So, we just added that piece of proof to his talk of introduction.

I’m Gary Gorman with Gorman and Associates CPA’s, and I help small businesses avoid IRS audits. In fact, in my career, I’ve helped clients complete over 3000 tax returns, and not a single one has ever been audited.

Here Is How I Adjust My Introduction Based on What I Want the Audience to Do.

For my proof, I have a number of options. Just like Gary, I have had a lot of clients who have had great successes. In addition, I have published two best-selling books about public speaking. I also have hundreds of thousands of people who listen to my podcast each week. So, I can pick my evidence based on what I want my audience to do.

For instance, if I’m speaking at a convention, and I want the audience to come by my booth to purchase my books, my introduction might sound like this.

Hi, I’m Doug Staneart with The Leader’s Institute ®, an international leadership development company, and I help people eliminate public speaking fear. One of the things that I’m most know for is being the author of two best-selling books, Fearless Presentations and Mastering Presentations.

However, if I’m leading a webinar, I may want the audience to purchase a seat in one of my classes. In that case, my introduction might sound like this.

Hi, I’m Doug Staneart with The Leader’s Institute ®, an international leadership development company, and I help people eliminate public speaking fear. For instance, for the last 20 years, I’ve taught public speaking classes to over 20,000 people, and I haven’t had a single person fail to reduce their nervousness significantly in just two days.

If my goal is to get the audience to subscribe to my podcast, my intro might sound like…

Hi, I’m Doug Staneart with The Leader’s Institute ®, an international leadership development company, and I help people eliminate public speaking fear. One of the ways that I do this is with my weekly podcast called, Fearless Presentations, which has over one million downloads, so far.

Use the Form Below to Organize How to Introduce Yourself in a Presentation.

The point is that you want to design your introduction in a way that makes people pause and think, “Really? That sounds pretty good.” You want to avoid introductions that make your audience think, “So what?”

If you have a speech coming up and need a good introduction, complete the form below. We will send you your answers via email!

Can You Replace Your Introduction with a PowerPoint Slide?

Is it okay to make your first slide (or second slide) in your presentation slides an introduction? Sure. A good public speaker will often add an introduction slide with a biography, portrait, and maybe even contact information. I sometimes do this myself.

However, I NEVER read the slide to my audience. I often just have it showing while I deliver the short introduction using the guide above. This is a great way to share more of your work experience without sounding like you are bragging.

For tips about how many powerpoint slides to use in a presentation , click here.

Remember that There Is a Big Difference Between Your Introduction in a Presentation and Your Presentation Starter.

When you introduce yourself in a presentation, you will often just use a single sentence to tell the audience who you are. You only use this intro if the audience doesn’t know who you are. Your presentation starter, though, is quite different. Your presentation starter should be a brief introduction with relevant details about what you will cover in your presentation.

For details, see Great Ways to Start a Presentation . In that post, we show ways to get the attention of the audience. We also give examples of how to use an interesting hook, personal stories, and how to use humor to start a presentation.

Podcasts , presentation skills

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20+ Self Introduction PowerPoint Templates: Download for free!

Think about the image you want to portray during your presentation pitch. Creativity? Soberness? Reliability? A professional PowerPoint design can help you deliver a powerful introduction to your stakeholders . 

Here, you'll find some creative Self-Introduction PowerPoint Templates that are going to elevate your slides to the next level. Our expert team has designed different layouts that you will surely love and save you a lot of time. 

And if you want to present your company and highlight your team's experience, you'll also find some fantastic Team Presentation Templates . Keep reading to get them all for free!

Introducing Yourself PowerPoint Templates

Introducing yourself is vital to generate a connection with your audience . In fact, it showcases your background and abilities, making sure you are the person they seek. 

That being said, let's have a look at the Self-Introduction PowerPoint Templates that we prepared for you and will optimize your creative process:

1. About Me PowerPoint Template

These self-introduction PowerPoint templates are perfect for anyone trying to convey sobriety and professionalism. 

The pack offers different layouts, which you can use to engage your audience and showcase your work experience. 

2. Personal Resume PowerPoint Template

This template is another great option for introducing yourself through a PowerPoint presentation. 

You'll find different types of diagrams and graphs that will display all your skills and work experience in a more eye-catching way. 

3. Colorful Resume PowerPoint Template

With this colorful template, you'll be able to create more impactful slides and add your desired background. 

It also includes a map that will help you showcase your experience abroad! 

4. Creative Resume PowerPoint Template

If you are not sure of the color palette of your presentation, try this blue template. It's the perfect color to convey professionalism!

This self-introduction PowerPoint template will definitely catch your audience's attention from the beginning. 

5. Personal Branding PowerPoint Template

This template is focused on Personal Branding, but you can use the graphics to organize your "About me" presentation in PowerPoint.

As always, we invite you to customize each element however you like!

6. Women Leadership Powerpoint Template

Want to be concise in your pitch? This template will inspire you!

As you can see in the image, you'll find a minimalist design of pink and purple tones.

7. Timeline Infographic PowerPoint Template

This template package has timelines and graphics that will be useful for organizing your personal information.

If you were looking for a modern and creative self-introduction template, this design may be for you!

8. User Persona PowerPoint Template

This PowerPoint template was initially designed to present Buyer Personas but can be adapted for an "About Me" section.

9. Photography Portfolio PowerPoint Template

Want to improve your portfolio? We've designed portfolio templates in PowerPoint, too!

This resource was created for photographers, but you can adjust it to your needs.

10. Career Portfolio PowerPoint Template

Here is another portfolio design in PowerPoint! 

When you download this template, you'll find a sober self-introduction design with blue tones.

We're not done yet!

In the following section, you'll discover more PowerPoint templates for introducing your work team to an audience.

Team Introduction PowerPoint Templates

Introducing your team becomes crucial when you want to attract new clients or investors to your business. It will spotlight your team's capabilities, convincing your audience that you can solve their problems. 

As always, all the slides in our templates are easily editable , so you can add any image you like and customize the aesthetics according to your color scheme .

Let's check the Team Introduction PowerPoint Templates we have for you: 

1. Team Slides PowerPoint Template

This team introduction PowerPoint template offers 8 different designs that will impress your audience. 

Pick the layout you like the most and add it to your presentation deck! 

2 . Roles and Responsibilities PowerPoint Template

This PowerPoint template is all about the roles and responsibilities of each team member.  

If you’re working on a new project, this team intro PowerPoint template will be perfect! 

3. Meet The Team PowerPoint Template

If you're seeking to introduce your company to a potential investor or client, check out these team introduction slides! 

This template pack will help you to present a complete overview of your business and the people involved in it.

4. Project Management PowerPoint Template

Do you have a project running and need to design the final presentation? This template is made for you!

As in the previous designs, you will find a project team slide template and more graphics that will make your presentation dazzle.

5. Strategic Action Plan PowerPoint Template

Here is another of our corporate templates to introduce your work team to an audience.

If you want designs with green and blue tones, this resource is for you!

6. Finance Team PowerPoint Template

This presentation contains animated slides with a fresh design.

When you download this PowerPoint template, you'll find a "mission and vision" section, a description of services, a customer profile, and more!

7. Light Corporate PowerPoint Template

Want to present a creative self-introduction but need more time to think about the design? If so, this template will be perfect for you.

You'll find a "meet the team" section, 3D graphics, infographics, and more. Download it for free now!

8. Creative Business PowerPoint Template

If you prefer a one-page self-introduction, take a look at this template.

It contains icons, timelines, statistical graphs, and more resources. Like the previous designs, the download is completely free!

9. Creative Pitchbook PowerPoint Template

This PowerPoint template and its unique designs will immediately catch your audience's attention.

If you want to convey professionalism and detail-oriented, this template pack is for you.

10. Film Pitch PowerPoint Template

These designs were created for film teams but can be adapted to any field!

We are confident its aesthetics will inspire you.

11. Storyboard Artist PowerPoint Template

Looking for more creative self-introduction slides? You'll love this one! 

Initially, this template is black and white, but you can edit the colors freely.

12. Team Introduction PowerPoint Template

This team introduction PowerPoint template has a unique format.

You'll be able to highlight your team's skills visually. And the best thing is that it's easy to understand at first glance!

13. Science Organization PowerPoint Template

A team introduction is always a great idea, but it's even better when you can showcase the relationship between different members and roles! 

With this template pack, you can make that possible.

Looking for Custom PowerPoint Presentations? We got you! 

If you liked our free template designs, you'll love 24Slides custom presentations ! 

A PowerPoint presentation is a great place to start making an excellent first impression. It will show your audience how committed you are to a project and how much effort you will put into it. 

But making a good PowerPoint presentation takes a lot of time and effort. Why not call upon professionals to handle it efficiently?

24Slides offers a pro-level design service that will elevate all your presentation decks. Our Designers have worked with some of the biggest companies worldwide, so we can offer the expertise you need. 

Still not sure? While working alongside us, you will: 

• Own high-impact presentations aligned with your brand – We help you communicate the message you want to convey!
• Choose between different services: Regular Service , Dedicated Design Teams , and Credit Packages – We adapt to your needs!
• Manage fast turnarounds – Go rest and get your presentation the following morning!
• Enjoy the process since we guarantee the confidentiality of your data – Your information is in good hands!
• Have the option to create a platform for connecting your Internal Team with our Designers – The integration will be seamless!

The best part is that you can try our expertise and style for just $1 . Our Designers will be happy to show you the true potential of your slides!

Found this content interesting? You'll love what's next: 

• 50+ Fun Icebreakers for Your Next Presentation
• 20+ Free PowerPoint and Google Slides Templates for Data Presentations
• How to Make a PowerPoint Template (Tutorial with Pictures!)
• Why is Brand Identity Important in Presentations? Experts answered!  
• The Cost of PowerPoint Presentations: Discover the hidden expenses you might overlook!

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How to Introduce Yourself in a Presentation: Guide to a Killer Opener

Hrideep barot.

• Body Language & Delivery , Speech Writing

Not sure how to introduce yourself in a presentation? Hang on till the end of this article.

Giving a presentation can be unnerving. And introducing yourself can be nerve-wracking.

But, without a fitting introduction, you would just be hitting the dart in a dark room.

The usual “Good Morning! I’m Neil, and I work as a Designer at…” is boring and doesn’t cut the ice anymore.

So, how to Introduce yourself in a presentation or start with a killer opener?

Introducing yourself in a presentation is pitching yourself to the audience so they stick around for the rest of your talk. Include your background, your unique trait, and who you are while sticking to the context in the first 30-60 seconds of your introduction.

Your introduction should be effective and have an interesting hook. You’ve got to nail your introduction in one shot.

A make or break moment indeed.

But, fret not! We’ve outlined what to say before starting a presentation to help get your next presentation right.

Occasions Where you Might Have to Introduce Yourself in a Presentation

Here is what to say to start a presentation on some of the occasions where you would have to introduce yourself before the presentation.

Though the principle focus will be about yourself, tweaking your intro to the context and the place is essential.

The self-introduction should be compelling enough to woo your audience to sit for the next couple of minutes.

1.How to Introduce Yourself in a Business Environment

Introducing yourself in your workplace can be rather common. But, it’s during business meetings and conferences where you need to stand out.

Every time you meet senior managers, introducing yourself with your name and job title doesn’t grab eyeballs anymore.

However, taking the first step matters. Here are certain scenarios where you might be called upon to introduce yourself in your workplace.

How to Introduce Yourself in an Interview Presentation

The “Tell me about yourself” in interviews is intimidating. If you’ve found alibi’s to every presentation in your school and college, it doesn’t work here anymore.

Prepare a short introduction about yourself and be interview-ready. Anytime someone hits you up with that question, you need to be able to answer it with the snap of a finger.

Here is an example of a self-intro during an interview.

“As a skilled designer, with two years of freelance experience, I’ve worked for clients with diverse needs. I’ve also designed brochures, magazines, logo , and packaging materials for my friend’s company. I’m confident that I can leverage my skills and bring in the best for your brand.

How to Introduce Yourself and Your Team in a presentation

Business meetings can be boring. But there are times where you might have to introduce yourself to a new co-worker or a senior leader.

As a team leader yourself, you might have to introduce yourself and your team to present on the performance of the company the previous month.

Presentation introduction ideas if you’re a marketing executive can be,

An increased conversion of 130%, that’s what our marketing team achieved last quarter making our campaign a massive success. The soldiers who made this possible are Ryan, who made sure the User Experience on our website was flawless. Sean who ensured seamless technical functioning, and Abby who is responsible for all the copies on our major assets. I’m John, who heads the marketing team and we want to take you through all the activities we actioned, the metrics we achieved, and the lessons we learned from our recent efforts.

In case you are giving a group presentation , you can check out this video to see how you can introduce different members of your group for seamless transitioning:

How to Introduce Yourself in a Conference Presentation

In a conference presentation, you’re expected to be a little formal. While you can adhere to that school of thought, don’t forget to story tell. That’s what hooks an audience! Here is an example of how to introduce yourself in a business conference:

“Today, I’m going to share a story of how someone with zero marketing skills and training made it to the top by creating massive revenue streams through online campaigns and paid advertising in just 6 months. If you’re passionate about digital marketing, this is for you. Stay tuned till the end for better insights.

If you’re presenting at a business conference, take a look at these 11 tips for presenting at a conference by Brian Campbell.

How to Introduce Yourself in a Business Pitch Presentation

Now, this is for entrepreneurs who are starting out. If you need investors to fund your start-up, you need to have a solid pitch.

 Let’s say, your product is AI-driven that alerts drivers who doze off while driving.

Talk about the benefits of it in a single sentence and highlight the downsides of dozing off while driving with stats and figures.

Check out this Crucial Public Speaking Tips for Startup Founders written by us that’ll help you nail your pitch.

Also, have a look at this video below. In this, Josh Light introduces himself in just two simple sentences and moves on to talk about his start-up. It is simple yet effective.

How to Introduce Yourself in Client Presentation

If you’re a freelancer, talking to clients can be a daunting task.

Let’s say you’re an engineer turned copywriter. That’s an interesting combo out there, and if you put it out in a way you write your copy, it would benefit you to a whole another level.

“I’m an experienced travel copywriter and I’ve written ad copies, sales pages, newsletters, landing pages for some of the top travel brands. I have over 5 years of expertise in this niche. One of my landing page copy at XYZ converted 50% of eyeballs into leads thus scaling up revenue drastically and I’m here to do the same if you see me fit after this call.”

2 . How to Introduce Yourself in a Presentation as a Student

Are you that kid/student who always shied away from giving presentations? Did you always come up with excuses and ended up giving barely one or two presentations your whole school life?

Yes? Well, it’s time to come out of your cocoon as it won’t work out that way in college or at work.

Whether it’s a small project presentation or giving a speech in your English class, here is how you can introduce yourself as a student.

How to Introduce Yourself in a Seminar Presentation

We’ve all been there. Hundreds of projects and assignments, be it school or college.

And that’s where you have to introduce yourself before jumping into your project. No matter how good your project, a solid introduction can put you ahead of the game.

“ As a tech enthusiast myself, I was intrigued by blockchain technology for a long time and today I have my project built using that very technology. I’m so excited to share with you all the working of this model and its benefits. Let’s jump right in.

It’s pretty easy and to-the-point. You need to be self-confident while saying those two lines and try to avoid fillers.

3. How to Introduce Yourself as a Trainer

As a trainer or teacher, your audience may be high-school students, undergrads, or even professionals.

Depending on the setting and the audience, you can craft your intro effectively and be of interest to the listeners.

How to Introduce Yourself to Students

As a teacher in a new school or college, introducing yourself is obligatory.

You can go about it this way if you’re a Moral Science teacher or Counselor:

“Hi everyone! I’m Alexandra. Call me Alex for short. We are going to have loads of fun for the next couple of months as I will be handling your Moral Science classes from today. If you are stuck in a dilemma or facing challenges, you can talk to me personally anytime and I’ll help you find a way out.

How to Introduce Yourself in a Workshop

Workshops are where you learn about a subject.  What if you’re the one who is conducting the workshop or needs to fill in for your friend for a couple of minutes, you need to introduce yourself.

 If you’re an Economics Graduate who is conducting a Calligraphy workshop, your presentation starting words can be something like,

  “Back when I was a kid, I used to scribble down letters I saw on posters and fell in love with the notion of lettering and calligraphy. I wanted to get into design, but I thought it was a fleeting moment and took Economics. Little did I know how much it meant to me. I finally figured what to do in life, and here I’m helping and teaching you to do what you love after years of learning and unlearning.”

How to Introduce Yourself in Training Sessions

Whether you’re a corporate trainer or getting into training students after years of experience, introducing yourself never gets old.

You can emphasize your past experiences in the form of a story or start with how it was when you worked with one of the top clients in the industry.

Below is an example to give you a precise picture.

“How excited are you to get your first gig? I’ve been a freelance writer for over a decade now. And freelancing is one of the best jobs as it gives you financial freedom and lets you work from the comforts of your couch or at your favorite café. So, I’m here to teach you to do the exact same thing and help you find your passion.”

5 . How to Introduce Yourself in a Video Presentation

Virtual presentations are a thing right now. If you’re a camera conscious person, you might have a hard time giving a presentation.

Dressing well and looking at the camera and not the screen can help present better. And always, look into the camera and not the screen when it comes to virtual presentations.

No matter how tensed you are, do not reflect it on your face. Have a bottle of water beside you to buy time and calm your nerves.

Here are two possible situations where you might have to introduce yourself virtually. 

How to Introduce Yourself in Webinars

Webinars are ever-increasing and if your introduction is not crisp and strong enough, building an online presence can be challenging.

Here is how you can introduce yourself in a webinar:

“ Hi, guys and welcome to this long-awaited session. How excited are you all? I know I am! We’re live and will be having John in a while. I’m so thrilled to see hundreds of you all attending this webinar live. It’s going to be a great session. I’m Patrick and the head of Marketing at XYZ. We started this webinar series two months ago and received phenomenal feedback from you all. And that’s why we’re back again with another one. Thank you and welcome again! Hope you find this session valuable.”

How to Introduce Yourself in a Virtual Presentation

Now, this is for freshers whose onboarding is going virtual. Whether it’s training sessions, virtual presentations, or virtual meetings, you are asked to introduce yourself to every manager and executive multiple times in a day.

Hey everyone! I’ve always loved meeting new people and though this is virtual now, just so thrilled to see you all on screen. If you see a new face popping on your screen during meetings and conferences, that’s me, John the new joinee. Can’t wait to meet you all in-person. Excited to jump-start my career here.

You can also check out this video we made to know certain ninja hacks to engage a virtual audience:

Related Article: All You Need To Know About Presenting Remotely

How to Structure an Intro – How to Start and End

• Add a Compelling Hook

You can begin your speech with a fact or a question to pique curiosity of your audience.

• A Brief Overview about Yourself

In those initial few seconds, greet the audience and talk about your strength or any unique trait in a word or two.

You can mention your achievements or contributions before talking about your background.

• A Quick history or Timeline of your Career/Education

In any context, a brief background or history about yourself should be talked about to let your audience know a little more about you.

It helps them gain trust and reliability.

• Smooth transition to the main topic

You shouldn’t abruptly move to the heart of your speech post introduction. There should be a subtle transition to make it effective.

Here is a presentation introduction example,

“Would you believe if I told you that you could reach 15k+ people on LinkedIn in just 30 days? No? Stick around for the next 7 minutes as I’m going to teach you all about it so you can get started as a rookie with zero connections.” Hi everyone! I’m XYZ – a Linked Growth Hacker. I’ve been helping businesses grow and build a strong personal brand for five years now. If you’re wondering how to generate leads on LinkedIn, take note of the pointers I’ll be sharing with you today.”

Magic ingredients to Introduce Yourself in a Presentation

You’ve got to nail your introduction no matter where you give the presentation.

You need to learn the art of introducing yourself because that’s the one thing you’ll be asked everywhere when you meet new people.

Introducing yourself is like marketing yourself. A stellar introduction can make a difference.

Here are some surefire ways to stand out in a crowd with your introduction.

With practice, your self-introduction will improve over time if you follow these tips. 

1 . Brevity is Key

We all know this by now. No matter how many years of experience you have or how much you’ve contributed to the team, your introduction should be short yet powerful.

With an impressive introduction about yourself, your audience will be keen on listening to you more. 

2 . Talk about Your Contribution

Instead of starting with your name and your job title, craft a story about the time you have to strive hard to achieve a goal be it personal or professional.

Speak about your contribution subtly without coming off as someone narcissistic. Unfold the little moments and share them with the audience.

Ensure it is related to your speech. Don’t go off course.  

3 . Understand Where You Are

The place where you present matters though it is about you. You need to research about the people, the place and craft an introduction aligning with it.

Keep it relatable. Get the audience to be on track with you. Keep your message clear and introduce it in a way it is memorable. 

4. Be as Real as Possible

Since you are introducing yourself, be as real as possible.

No, you don’t have to be extremely personal, but you can keep it minimal and include a common ground so that the audience can resonate with you.

5. A Smooth Transition is Essential

Transitioning from your intro to the main speech needs to be done right to keep the flow going.

Craft an intro and shift to the main topic without a pause after the introduction.

6. Create a Hook

Creating a hook is essential no matter the setting you’re introducing yourself in.

You need to grab the attention of the audience with your first sentence. You can quickly introduce yourself in a few sentences without taking much time.

Begin with a question or an interesting fact to hook the listeners every time you introduce yourself.

Want some inspiration? Here is a very practical video we have made on different opening lines from some of the most powerful speeches. Hopefully, it will get your creative juices flowing for what your hook should be:

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Concluding Thoughts

Introducing yourself in a presentation can be stressful. You won’t get it right on your first. Nope. Not on your third attempt.

Heck! Not even on your sixth introduction too.

But, here’s the thing.

You need to keep sailing and believe in yourself. That’s what can make you better.

If you want to evolve as an individual, learning how to introduce yourself can immensely contribute to your professional and personal growth.

Push your boundaries and cross your personal threshold. You will get there one day. And introducing yourself will no longer be a daunting task.

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8 Effective Ways to Introduce Yourself in a Presentation

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Several studies have shown that you only have 7 seconds to make an everlasting impression on your audience in a presentation. It means these few seconds are critical as your audience makes a subconscious decision of whether what you speak is worth listening to or not. 

Presenters generally begin a presentation with their self-introduction, and those 7 seconds cover-up in explaining about them. So, it’s important to make this part of your talk more powerful and captivating.

Self-introduction is not as easy as it seems to be. You would want to highlight your achievements, but at the same time, you won’t want to blow your trumpet. You would not want to share every minute detail about your life, but you won’t want to miss out on telling any important thing about yourself to the audience either. In a nutshell, when you have to introduce yourself, you are in a dilemma – what to say and what not to say.

In this article, we have provided you with some tips and ways to overcome this dilemma and make your self-introduction memorable. Let’s start!

Why is Self-Introduction Important?

A self-introduction is an easy way to start a conversation. You get the opportunity to highlight your skills, educational background, interests, and experience. In short, it gives a brief idea about your personality. Also, this part sets the tone for your entire presentation. Hence it should be compelling enough to woo your listeners.

Creative Ways to Introduce Yourself to the Audience

1. start with your name and background information.

Though this is an age-old way of self-introduction, it’s always in trend and most preferred by global presenters.

State your name, the organization you are representing, the position you hold, and some facts that give a concise idea about your personality.  

For example, you can start in this manner-

“Greetings, I am Stella Harris working for XYZ Company for the past 6 years.”

2. Tell Your Personal Tagline

A tagline is a catchphrase that tells the audience about the value/service you create for the customers. 

Just like big brands create a tagline to increase their product awareness,  you can use this idea to highlight your strength and passion in a single statement. Craft a personal tagline that is catchy, precise, memorable, and customer-oriented.

Here are some tips on how to create a personal tagline for yourself.

• Do a self-assessment and identify your strengths and achievements.
• Assess your skills, values, and passion.

Now brainstorm the above points and jot down the words that best describe you.  Choose the main keyword and phrase a catchy one-liner around that keyword. Don’t forget to keep it short. 

3. A Punchy Elevator Pitch

Sharing your unique strengths, key skills, and abilities all in one go is quite a challenge. An elevator pitch is one of the best ways to connect with a new audience and communicate the value you can create for them. An elevator pitch is a short description of who you are and what you do within a time span of 30 seconds or less. 

While writing an elevator pitch, be sure to keep it goal-oriented and add a hook to reel the audience’s attention in a jiffy.

4. Share a Less-Known Fact About Yourself

Find out what makes you stand out from the crowd. Highlight your unique work experience.

For example, you can share with the audience that “In my job, I have had the opportunity to work with several kinds of people. This allowed me to understand different work styles. And, with time, I have gained amazing leadership and team-building skills. In the past 2 years, I have successfully completed XYZ number of projects.”

5. Tell a Quote that Best Describes You

Quotes are a powerful way of expressing your strongest persona. Using them in your self-introduction can help you connect quickly with a larger audience.

For example, you can begin with any of these quotes and then explain how this quote best reflects your personality.

“You are what you think.”

“You will never change your life until you change something you do daily. The secret of your success is found in your daily routine.” – John C. Maxwell, American author

6. Highlight Your Expertise that is Applicable to the Audience

The skills that you share should be audience-focused. Hence, you need to be very clear about what your audience wants from your presentation beforehand. Share your key credentials that can build a good rapport with your listeners.

7. Share Similarities

Shared interests contribute to the formation of new networks. When you share your interests and similarities with other people in a presentation, it engages the audience till the last minute. Also, it encourages more participation and conversation, which results in the ultimate success of the presentation.

8. Tell a Story

Starting off a presentation with a short personal story takes your audience on a journey that you have traveled. It reveals the passion for your work, the struggles you faced, and how you dealt with the challenges. But before you jumpstart on storytelling, you must know the audience’s pain points. It will evoke empathy and build trust because they will be able to easily relate to your story.

Some Quick Tips 

• Don’t brag while talking about yourself.
• Thoughtfully organize and rehearse your self-introduction.
• Know your audience, their pain points, and interests. Create your self-introduction based on that information.
• Be authentic while sharing any facts about yourself.
• Use a conversational tone while speaking to establish a quick connection with your audience. 

To Conclude

Introducing yourself is itself a nerve-wracking task. And, if you have to give a speech in front of an unfamiliar group, it may break you out in a cold sweat. The whole point of self-introduction is to make your audience familiar with you and make them understand why it is worth it for them to stay and listen. Starting your presentation with a well-prepared, engaging, and powerful self-introduction can help you build a relationship of trust with your listeners from the very first moment. 

For a more impactful self-introduction, you can use pre-designed PowerPoint templates and let your personality shine through creative slides.

Follow the above-mentioned ways outlined in this blog and make a mark while introducing yourself in the next presentation.

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How to Introduce Yourself in a Presentation

Last Updated: October 4, 2023 Fact Checked

This article was co-authored by Patrick Muñoz . Patrick is an internationally recognized Voice & Speech Coach, focusing on public speaking, vocal power, accent and dialects, accent reduction, voiceover, acting and speech therapy. He has worked with clients such as Penelope Cruz, Eva Longoria, and Roselyn Sanchez. He was voted LA's Favorite Voice and Dialect Coach by BACKSTAGE, is the voice and speech coach for Disney and Turner Classic Movies, and is a member of Voice and Speech Trainers Association. There are 11 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 127,257 times.

Introducing yourself in a presentation is more than just saying your name. It’s an opportunity for you to share relevant details about yourself and connect with your audience. It also sets the tone for the rest of the talk. How you introduce yourself will influence how your audience receives the message you want to get across. Make your next introduction flawless by presenting the most engaging information about yourself. Be sure to prepare the introduction in advance and start with an attention-grabbing technique to connect to the audience.

Including Relevant Information in Your Introduction

• If you have an unusual or difficult to pronounce name, you may want to add a small remark to help your audience remember it. For example, you can say “My name is Jacob Misen, like ‘risen’ but with an M.”
• Try to make eye contact with parts of audience during your presentation as well. [1] X Research source

• If you are VP of Marketing at a large company, it can actually be much more effective to say something like “I have more than a decade of experience using Facebook marketing ads to target clients in the dance industry” rather than simply stating your job title.

• You can also specifically refer your audience to the handout or powerpoint for more information. For example, if you want to let them know that you have articles in many international newspapers but you don’t want to list them all out, simply say “I’ve written for a number of internationally recognized news organizations. You can find the full list on the first page of my handout.”

• For example, you could say “when I designed a website for Richard Branson last year …” to inform your audience that you have an impressive resume, without having to list it all for them in your introduction.

• Try concluding your introduction by mentioning a client or project you were working on that directly relates to the topic of your presentation. For example: “I’ve had the pleasure of working with NXP Semiconductors for the past three years. Just last week we encountered a problem with our logistical database...” and then lead into your presentation about a new software that will solve everyone’s logistical hiccups.

Grabbing Your Audience’s Attention Before Your Introduction

• If you don’t have music that can tie to your presentation, you can use a song with the theme of beginning. For example, if you are presenting at a sales meeting, play some soft jazz as participants enter. Then, when it’s time for you to start, play the Black Eyed Peas chorus of “Let’s Get it Started” to get your audience’s attention. You can then open with an energetic “Good morning!” or “Good Afternoon” as the music ends.
• Remember to choose music that’s appropriate to the event. An academic conference may not be the best place for pop music, for example (unless you are presenting research on pop music, of course).

• For example, if you are presenting on the design of a new user-friendly coffee machine, you may start your presentation by referencing Elon Musk: “Any product that needs a manual to work is broken,” and then go on to say “My name is Laurie Higgens, and my coffee machine doesn’t come with a manual.” Speak briefly about your relevant experience and qualifications, and then dive into presenting your design.
• Avoid cliche or overused motivational quotes the audience has probably already heard many times.
• Be sure to correctly cite your quote.

• For example, you might start with “According to Time magazine, Americans filled 4.3 billion prescriptions and doled out $374 billion on medicine in 2014.” Then, introduce yourself and your qualifications in medical research and transition into a presentation about how to prevent doctors from over prescribing medication to their patients.
• Remember to cite the source of your statistics. You will look more professional and reliable, and the audience will be able to follow up on the information if they wish.

• If you are giving a presentation about a new airport security-friendly travel bag, try starting your presentation with “How many of you have ever stood in line at airport security and nearly missed your flight?”
• You can also invite your audience to close their eyes and imagine something as you lead up to your question.
• Don’t be discouraged if your audience doesn’t raise their hands when you ask a question. Sometimes these questions seem more rhetorical to an audience, or maybe they are just shy. You can often see signs that they are still engaging with the question if people are nodding or smiling after you ask it.

• Try telling stories, showing pictures on a powerpoint, or using quotations.
• Being funny not only puts your audience at ease, but it also helps them remember you after the presentation. [10] X Research source

• For example, if you are making a presentation about a pizza delivery app, ask your audience members to tell their name, their favorite pizza topping, and a situation where they’ve had a particularly amazing or awful experience with food delivery.

Preparing Before Your Presentation

• When it’s time to present, it’s probably best to just write down a few notes or key words to remind you of what you want to say so you don’t just read off your note cards.
• Think about your overall intention as a speaker. Are you trying to educate, enlighten, or entertain the audience? Figure out the effect you want to have on the listener so your presentation is impactful.

• If you don’t have a friend to watch your presentation, record yourself on video and play it back later to refine your presentation skills. It can be uncomfortable to watch yourself on video, but it will help you nail your introduction. You can even record your whole presentation. Keep recording and re-recording until you are happy with it. Then you know the audience will be happy too.

• The best resource to learn about the local culture is the locals themselves. If you have a contact where you will be speaking, ask them about customs, dress code, and how humor is usually received. If you don’t know anyone personally, try searching in industry-specific online forums. Find YouTube videos of presentations given in the area that are relevant to your industry.

What Is The Best Way To Start a Presentation?

Expert Q&A

• Don’t spend too much time introducing yourself. Your introduction should be short and to the point so you can get on to your main presentation material. Depending on the length of your presentation, your introduction should be between 20 seconds and 2 minutes long. Thanks Helpful 1 Not Helpful 0

You Might Also Like

• ↑ https://www.canr.msu.edu/news/eye_contact_tips_to_make_your_presentations_stronger
• ↑ https://www.indeed.com/career-advice/career-development/introduce-yourself-professionally
• ↑ https://www.washington.edu/doit/presentation-tips-0
• ↑ https://www.gvsu.edu/ours/oral-presentation-tips-30.htm
• ↑ https://www.forbes.com/sites/forbescoachescouncil/2018/09/27/15-hacks-for-making-your-presentation-more-creative-and-engaging/
• ↑ https://www.hamilton.edu/academics/centers/oralcommunication/guides/how-to-engage-your-audience-and-keep-them-with-you
• ↑ https://www.linkedin.com/pulse/make-em-laugh-ten-tips-using-humor-presentations-judy-romano-mba?trk=portfolio_article-card_title
• ↑ https://www.ncsl.org/legislators-staff/legislative-staff/legislative-staff-coordinating-committee/tips-for-making-effective-powerpoint-presentations.aspx
• ↑ https://crln.acrl.org/index.php/crlnews/article/view/19102/22119
• ↑ https://www.forbes.com/sites/tjwalker/2011/06/07/should-i-rehearse-and-for-how-long-presentation-training/

About This Article

To introduce yourself at the start of your presentation, all you need to do is state your name and tell the audience any relevant experience or skills you have. For example, say something like, “My name is Jacob Misen, and I have over a decade of experience using Facebook marketing ads in the dance industry.” If you have a broad range of relevant experience, you can bullet point a few examples on your opening slide instead of reading them out. Once you’ve introduced yourself, smoothly transition into your presentation. For instance, you can mention a client or project you’ve recently worked on that relates to the topic of your presentation. For more tips, including how to practice your presentation, read on! Did this summary help you? Yes No

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Top 10 Introducing Yourself Templates with Examples and Samples

Kavesh Malhotra

"The difference between ordinary and extraordinary is that little extra," Jimmy Johnson, American sports coach.

Jimmy Johnson's words perfectly fit when it comes to introducing yourself. A personal introduction is a part of almost every career option you pick today. How you introduce yourself can open or close the doors of opportunities for you. When you have a killer introduction, people will remember you. It sets the stage for more interactions, showcases your confidence, and helps others understand you better. 

Let's say you are pitching for funding for your business. But before you introduce your product in front of the investors, they would love to know where they are putting their money into. In such cases, an outstanding introduction gives you an opportunity to establish a killer rapport from the beginning. It adds credibility from the get-go. Similarly, if you are attending a networking event or attending a job interview, an impactful self-introduction goes a long way in boosting your chances for success.

At Slide Teaml, our experts have prepared self-introduction templates after much analysis and studying human psychology. These 100% content-ready templates are fully editable and give you the ability to present yourself in a much more impactful and creative way. Using these templates, you can transform your routine introduction into a powerful self-endorsement. 

Let's take a look at these templates one by one.

Template 1: Introduce Yourself PowerPoint Presentation Slides

This template acts as a powerful tool for creating a powerful personal introduction . It includes a wide range of slides that can help you express your strengths in a much more engaging and effective way. The slides include About Me, Career, SWOT Analysis , Qualifications, and more. Each slide is highlighted by engaging visual icons for milestones, skills, hobbies, and more. The attractive color palate makes the template even more indulging and ensures no one bats an eye when you are introducing yourself. This helps craft a powerful story that talks about your skills and prowesses. It's perfect for interviews and networking and can help create a strong and impactful first impression for yourself.

Download Now

Template 2: Introducing Yourself and Your Capabilities in a PowerPoint Presentation with Slides

This template can be an amazing tool to create a strong first impression in any professional setting. The multi-slide template lets you highlight your personal and professional qualities in a well-structured and powerful way. Its key elements, like a detailed About Me section, a Career Timeline, a Personal SWOT Analysis , and a vivid Personal Profile slide, touch upon every aspect of your self-introduction. The clean and clutter-free design, with its bold color accents and smart graphics, ensures that your strengths and potential are properly highlighted. This template is perfect for job interviews, networking events, and team introductions.

Template 3: 10 Minutes Presentation About Myself PowerPoint Presentation Slides

This template is specifically crafted for professionals who want to make a strong first impression in a brief interaction. It helps you build a powerful narrative about your career path, personal strengths, educational background, and professional accomplishments.

The vibrant green with dark hues helps grab attention, while perfectly organized content blocks ensure the information is digested properly by the audience. Some of the key slides, like the Career Timeline and SWOT Analysis slides, help present a crisp and dynamic view of your professional journey and personal analysis.

Template 4: Introducing Yourself, Employee Achievement, Team Member Candidate Skills

This is a perfect template if you want to shed some light on your individual strengths and team contributions. The sections like "Employee Achievement Timeline in Introducing Yourself" and "Essential Candidate Characteristics in Introducing Yourself"  could be a killer way to tell others about your abilities and yourself. The engaging visuals let you present your career progression, key qualifications, and notable achievements. It’s a perfectly balanced mix of imagery and icons that enhance recall and engagement. In short, this template is a great choice for job candidates and team members who want to showcase their skills as an individual and as a team member.

Template 5: Meeting New People and Introducing Yourself PowerPoint Presentation Slides

Meeting someone for the first time and want to nail the first impression? This template can get the job done! It's tailor-made for job seekers and professionals who are looking for growth in their careers. This template offers a structured layout to showcase one's career journey, skillset, and achievements. The 'About Me/Bio' slide allows for a personal touch, integrating an image with key personal details. 'Agenda' and 'Career Objective' slides lay out a crisp outline to showcase the presenter's goals. The template has a soothing color scheme and ensures readability and a professional aesthetic. Download now and create memorable information.

Template 6: SWOT Analysis

When introducing yourself, you have to present your strengths in front of your audience. But at the same time, you cannot go praising yourself from the start! Instead, a balanced approach goes a long way. And the best way to do so is to present a SWOT analysis of your own! That's where this template comes into play. It has color-coded quadrants that provide intuitive self-assessment for the views. The vibrant red color covers strengths, professional blue for weaknesses, growth-associated greens for opportunities, and cautionary greys for threats. Additionally, the magnifying glass symbolizes the focus and introspection you have done to prepare this analysis. 

Template 7: Career Objectives

When you are talking about your career objective , it should feel more like a realistic plan instead of daydreams. And this template can help you articulate your objective pretty neatly. Designed with bold colors and direction-pointing arrow signs, this template features a profession over the years and a clear roadmap for the future. It encourages a step-by-step approach to set goals from foundational intentions to long-term objectives and strategic choices. You can effectively express your career vision and align your goals with action. You can demonstrate a forward-thinking mindset and an organized approach to career planning using this template. 

Template 8: Case Study

This template is an excellent option if you are presenting a case study to introduce your problem-solving skills. How? Well, this one lets you showcase how you were able to tackle a particular set of challenges that crept up while working on it. When you showcase a real-life example, it gives the viewers more confidence in you. The design is sleek, and a balanced use of space and contrasting colors grab the audience's attention. It helps them focus on the areas that matter the most. The central image acts as an anchor, and the surrounding icons help simplify complex information. Each icon acts as a visual marker with space to add necessary information about the particular case study.

Template 9: Introducing Yourself Depicting Employee Performance

Professional achievements are always a key part of self-introduction, especially for those who are looking to crack an interview. This template is specifically designed for such individuals. This template has a prominent section for the presenter's profile photo, a detailed education history , and work experience. It features a 'Skill Data Statistic' section with customizable gauges. This section can help you visually represent what expertise you have in particular skills. This template is a perfect blend of personal branding and performance metrics that's suitable for interviews, performance reviews, or personal assessments.

Template 10: Career Path

A career is nothing less than climbing steps, right? This template visualizes the career journey with clarity and motivation, using the same concept. With a staircase graphic that represents a step-by-step progression and a trophy at the end that indicates the ultimate goal, this template is a great career path presentation template. Here, each step of the staircase acts as a distinct phase or accomplishment in your professional career. The silhouette of a person at the base adds a human element to the narrative. This editable slide is perfect for professionals outlining career goals, milestones, or success stories during presentations.

The Final Thought

Your initial introduction can make or break your deal or interview, so it's always better to have a rock-solid first impression whenever you meet someone. These templates could be of great assistance in such cases and help you connect with the audience at professional levels. Download them now and make your introductions more attractive and crystal clear. 

Related posts:

• Top 10 Templates for Presentation About Myself with Samples and Examples
• Top 10 Self-Introduction Templates with Samples and Examples
• Must-Have About Me Introduction Samples With Examples and Templates
• Top 5 Professional Profile Templates with Examples and Samples

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A Simple Way to Introduce Yourself

by Andrea Wojnicki

Summary .   

Many of us dread the self-introduction, be it in an online meeting or at the boardroom table. Here is a practical framework you can leverage to introduce yourself with confidence in any context, online or in-person: Present, past, and future. You can customize this framework both for yourself as an individual and for the specific context. Perhaps most importantly, when you use this framework, you will be able to focus on others’ introductions, instead of stewing about what you should say about yourself.

You know the scenario. It could be in an online meeting, or perhaps you are seated around a boardroom table. The meeting leader asks everyone to briefly introduce themselves. Suddenly, your brain goes into hyperdrive. What should I say about myself?

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Free Self Introduction Powerpoint Templates And Google Slides

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Self Introduction PowerPoint Templates

Individuals can use self-introduction slides for PowerPoint to help to create a first impression on their audience.

With Self Introduction PowerPoint templates, candidates and individuals can demonstrate their experience and capabilities, showcase their educational background, and highlight their skills while pursuing a new job position.

Individuals can also present their contact information and resume concisely and elegantly while applying for a new job opening, increasing the chances for hiring managers to keep an eye on them. Individuals can also use the self-introduction PowerPoint templates to prepare group meetings and workshops.

Featured Templates

Self Introduction PowerPoint Template

Personal Self Introduction PowerPoint Template

Creative Self Introduction Slide Template for PowerPoint

Simple User Profile PowerPoint Template

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About Me Slide Template for PowerPoint

All About Me PowerPoint Template

Animated Student Intro PowerPoint Template

Multi-Slide Resume PowerPoint Template

Modern Resume Presentation Template

In this section, you can find 100% editable introduction slides for presentations, for self-introduction or presenting yourself. Do you want to know how to introduce yourself? Using the self-introduction and about me slides can help to prepare a presentation for a self-introduction. Alternatively, learn how to start a presentation to understand what are the key elements to include at the beginning of a presentation.

How do you introduce yourself?

You can reuse one of the Self Introduction PowerPoint templates to create a compelling presentation in PowerPoint (or Google Slides) with introduction slides.

The slides can contain a photo, the descriptions and visual aids to present your skill levels, experience and background.

How do you introduce yourself in an interview?

Using resume templates and self introduction slides, you can make a PDF or presentation in PowerPoint to introduce yourself during an interview. Our 100% editable self-introduction templates can help to present your skills, backgrounds and contact information.

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Self Introduction for a Job Interview

It seems that you like this template, self introduction for a job interview presentation, free google slides theme, powerpoint template, and canva presentation template.

Are you preparing for an important job interview? You can either use this Google Slides & PowerPoint template to make a lasting impression by doing a self-introduction, or you can use it to prepare something akin to a résumé! There are elegant geometric shapes and gradients, so the "grabbing attention" box can be ticked. Have a look at this design and, if necessary, make the most of the cover letter included, or add more shapes, since we've included more of them in the final slides as extra resources!

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50 Inspiring Examples: Effective Self-Introductions

By Status.net Editorial Team on September 22, 2023 — 19 minutes to read

• Structure of a Good Self-introduction Part 1
• Examples of Self Introductions in a Job Interview Part 2
• Examples of Self Introductions in a Meeting Part 3
• Examples of Casual Self-Introductions in Group Settings Part 4
• Examples of Self-Introductions on the First Day of Work Part 5
• Examples of Good Self Introductions in a Social Setting Part 6
• Examples of Good Self Introductions on Social Media Part 7
• Self-Introductions in a Public Speaking Scenario Part 8
• Name-Role-Achievements Method Template and Examples Part 9
• Past-Present-Future Method Template and Examples Part 10
• Job Application Self-Introduction Email Example Part 11
• Networking Event Self-Introduction Email Example Part 12
• Conference Self-Introduction Email Example Part 13
• Freelance Work Self-Introduction Email Example Part 14
• New Job or Position Self-Introduction Email Example Part 15

Part 1 Structure of a Good Self-introduction

• 1. Greeting and introduction: Start by greeting the person you’re speaking to and introducing yourself. For example, “Hi, my name is Jane. Nice to meet you!”
• 2. Brief personal background: Give a brief overview of your personal background, such as where you’re from or what you do. For example, “I’m originally from California, but I moved to New York a few years ago. I work in marketing for a tech company.” Related: 10 Smart Answers: “Tell Me About Yourself”
• 3. Professional experience: Highlight your relevant professional experience, including your current or previous job titles and any notable achievements. For example, “I’ve been working in marketing for about 5 years now, and I’m currently a Senior Marketing Manager at my company. Last year, I led a successful campaign that resulted in a 20% increase in sales.” Related: How to Describe Yourself (Best Examples for Job Interviews)
• 4. Skills and strengths: Mention any skills or strengths that are relevant to the conversation or the situation you’re in. For example, “I’m really passionate about data analysis and using insights to inform marketing strategy. I’m also a strong communicator and enjoy collaborating with cross-functional teams.” Related: 195 Positive Words to Describe Yourself [with Examples] 35 Smart Answers to “What Are Your Strengths?” What Are Your Strengths And Weaknesses? (Answers & Strategies)
• 5. Personal interests: Wrap up your self-introduction by mentioning a few personal interests or hobbies, which can help to humanize you and make you more relatable. For example, “In my free time, I love hiking and exploring new trails. I’m also a big fan of trying out new restaurants and cooking at home.”
• Related: Core Values List: 150+ Awesome Examples of Personal Values Best Examples of “Fun Facts About Me” What Are Your Values? How to Discover Your Values

Part 2 Examples of Good Self Introductions in a Job Interview

Try to cover these aspects:

• Current or most recent position/job
• A relevant accomplishment or strength
• Why you are excited about the company or role

Templates and Scripts

“Hello, my name is [Your Name], and I recently worked as a [Your Most Recent Position] at [Company/Organization]. I successfully managed a team of [Number] members, achieving a [Relevant Accomplishment or Growth]. I’m excited about the opportunity at [Interviewer’s Company] because [Reason Why You’re Interested].”

“Hi, I’m [Your Name], a [Current Job Title or Major Accomplishment]. I’m passionate about [Relevant Industry or Skillset] and have a proven track record of [Specific Result or Achievement]. I believe my skills and experience make me well-suited for this role at [Company], and I’m excited to explore how I can contribute to [Company Goal or Project].”

“Hi, my name is Jane Doe, and I’m the Assistant Marketing Manager at ABC Corp. I recently implemented a successful social media campaign, which increased engagement by 30%. I’m thrilled about the possibility of working with XYZ Inc. because of your innovative marketing strategies.”

“Hello, I’m John Smith, a financial analyst with five years of experience in the banking industry. I’ve consistently exceeded sales targets and helped my team win an award for excellent customer service. I’m excited to join DEF Ltd. because of your focus on sustainable and responsible investing.”

Try to tailor your introduction to the specific interview situation and always show enthusiasm for the position and company. This will show the interviewer that you are the right fit.

Related: How to Describe Yourself (Best Examples for Job Interviews)

Part 3 Examples of Good Self Introductions in a Meeting

General tips.

• Start with a greeting: Begin with a simple “hello” or “good morning.”
• State your name clearly: Don’t assume everyone knows you already.
• Mention your role in the company: Help others understand your position.
• Share relevant experience or accomplishments: Give context to your expertise.
• Be brief: Save detailed explanations for later conversations.
• Show enthusiasm: Display interest in the meeting and its objectives.
• Welcome others: Encourage a sense of connection and camaraderie.
• Basic introduction : Hi, I’m [Name], and I work as a [Your Role] in the [Department]. It’s great to meet you all.
• Involvement-focused : Good morning, everyone. I’m [Name], [Your Role]. I handle [Responsibility] in our team, and I’m looking forward to working with you on [Project].
• Experience-based : Hello! My name is [Name] and I’m the [Your Role] here. I’ve [Number of Years] of experience in [Skills or Industry], so I hope to contribute to our discussions during the meeting.
• New team member : Hi, I’m [Name]. I just joined the [Department] team as the new [Your Role]. I have a background in [Relevant Experience] and am excited to start working with you on our projects!
• External consultant : Hello everyone, my name is [Name], and I’m here in my capacity as a [Your Role] with [Your Company]. I specialize in [Skill or Industry], and I’m looking forward to partnering with your team to achieve our goals.
• Guest speaker : Good morning, I’m [Name], a [Your Position] at [Organization]. I have expertise in [Subject], and I’m honored to be here today to share my insights with you.

Related: 10 Smart Answers: “Tell Me About Yourself”

Part 4 Examples of Casual Self-Introductions in Group Settings

Template 1:.

“Hi, I’m [your name], and I’m a [profession or role]. I love [personal hobby or interest].”

“Hi, I’m Emily, and I’m a pediatric nurse. I love gardening and spending my weekends tending to my colorful flower beds.”

“Hello, I’m Mark, and I work as a data analyst. I love reading science fiction novels and discussing the intricacies of the stories with fellow book enthusiasts.”

“Hey there, I’m Jessica, and I’m a chef. I have a passion for traveling and trying new cuisines from around the world, which complements my profession perfectly.”

Template 2:

“Hey everyone, my name is [your name]. I work as a [profession or role], and when I’m not doing that, I enjoy [activity].”

“Hey everyone, my name is Alex. I work as a marketing manager, and when I’m not doing that, I enjoy hiking in the wilderness and capturing the beauty of nature with my camera.”

“Hello, I’m Michael. I work as a software developer, and when I’m not coding, I enjoy playing chess competitively and participating in local tournaments.”

“Hi there, I’m Sarah. I work as a veterinarian, and when I’m not taking care of animals, I enjoy painting landscapes and creating art inspired by my love for wildlife.”

“Hi there! I’m [your name]. I’m currently working as a [profession or role], and I have a passion for [hobby or interest].”

“Hi there! I’m Rachel. I’m currently working as a social worker, and I have a passion for advocating for mental health awareness and supporting individuals on their journeys to recovery.”

“Hello, I’m David. I’m currently working as a financial analyst, and I have a passion for volunteering at local animal shelters and helping rescue animals find their forever homes.”

“Hey, I’m Lisa. I’m currently working as a marine biologist, and I have a passion for scuba diving and exploring the vibrant underwater ecosystems that our oceans hold.”

Related: 195 Positive Words to Describe Yourself [with Examples]

Part 5 Examples of Good Self-Introductions on the First Day of Work

• Simple Introduction : “Hi, my name is [Your name], and I’m the new [Your position] here. I recently graduated from [Your university or institution] and am excited to join the team. I’m looking forward to working with you all.”
• Professional Background : “Hello everyone, I’m [Your name]. I’ve joined as the new [Your position]. With my background in [Your skills or experience], I’m eager to contribute to our projects and learn from all of you. Don’t hesitate to reach out if you have any questions.”
• Personal Touch : “Hey there! I’m [Your name], and I’ve recently joined as the new [Your position]. On the personal side, I enjoy [Your hobbies] during my free time. I’m looking forward to getting to know all of you and working together.”

Feel free to tweak these scripts as needed to fit your personality and work environment!

Here are some specific examples of self-introductions on the first day of work:

• “Hi, my name is Alex, and I’m excited to be the new Marketing Manager here. I’ve been in the marketing industry for five years and have worked on various campaigns. Outside of work, I love exploring new hiking trails and photography. I can’t wait to collaborate with you all.”
• “Hello, I’m Priya, your new Software Engineer. I graduated from XYZ University with a degree in computer science and have experience in Python, Java, and web development. In my free time, I enjoy playing the guitar and attending live concerts. I’m eager to contribute to our team’s success and learn from all of you.”

Related: Core Values List: 150+ Awesome Examples of Personal Values

Part 6 Examples of Good Self Introductions in a Social Setting

Casual gatherings: “Hi, I’m [Name]. Nice to meet you! I’m a huge fan of [hobby]. How about you, what do you enjoy doing in your free time?”

Networking events: “Hello, I’m [Name] and I work as a [profession] at [company]. I’m excited to learn more about what everyone here does. What brings you here today?”

Parties at a friend’s house: “Hi there, my name is [Name]. I’m a friend of [host’s name] from [work/school/etc]. How do you know [host’s name]?”

• Casual gathering: “Hey, my name is Jane. Great to meet you! I love exploring new coffee shops around the city. What’s your favorite thing to do on weekends?”
• Networking event: “Hi, I’m John, a website developer at XY Technologies. I’m eager to connect with people in the industry. What’s your field of expertise?”
• Party at a friend’s house: “Hello, I’m Laura. I met our host, Emily, in our college photography club. How did you and Emily become friends?”

Related: Best Examples of “Fun Facts About Me”

Part 7 Examples of Good Self Introductions on Social Media

• Keep it brief: Social media is fast-paced, so stick to the essentials and keep your audience engaged.
• Show your personality: Let your audience know who you are beyond your job title or education.
• Include a call-to-action: Encourage your followers to engage with you by asking a question or directing them to your website or other social media profiles.

Template 1: Brief and professional

Hi, I’m [Your Name]. I’m a [Job Title/Field] with a passion for [Interests or Hobbies]. Connect with me to chat about [Subject Matter] or find more of my work at [Website or Social Media Handle].

Template 2: Casual and personal

Hey there! I’m [Your Name] and I love all things [Interest or Hobby]. In my day job, I work as a [Job Title/Field]. Let’s connect and talk about [Shared Interest] or find me on [Other Social Media Platforms]!

Template 3: Skill-focused

Hi, I’m [Your Name], a [Job Title/Field] specializing in [Skills or Expertise]. Excited to network and share insights on [Subject Matter]. Reach out if you need help with [Skill or Topic] or want to discuss [Related Interest]!

Example 1: Brief and professional

Hi, I’m Jane Doe. I’m a Marketing Manager with a passion for photography and blogging. Connect with me to chat about the latest digital marketing trends or find more of my work at jdoephotography.com.

Example 2: Casual and personal

Hey there! I’m John Smith and I love all things coffee and travel. In my day job, I work as a software developer. Let’s connect and talk about adventures or find me on Instagram at @johnsmithontour!

Example 3: Skill-focused

Hi, I’m Lisa Brown, a Graphic Designer specializing in branding and typography. Excited to network and share insights on design. Reach out if you need help with creating visually appealing brand identities or want to discuss minimalistic art!

Part 8 Self-Introductions in a Public Speaking Scenario

• Professional introduction: “Hello, my name is [Your Name], and I have [number of years] of experience working in [your field]. Throughout my career, I have [briefly mention one or two significant accomplishments]. Today, I am excited to share [the main point of your presentation].”
• Casual introduction: “Hey everyone, I’m [Your Name], and I [briefly describe yourself, e.g., your hobbies or interests]. I’m really thrilled to talk to you about [the main point of your presentation]. Let’s dive right into it!”
• Creative introduction: “Imagine [paint a visual with a relevant story]. That’s where my passion began for [the main point of your presentation]. My name is [Your Name], and [mention relevant background/information].”
• Professional introduction: “Hello, my name is Jane Smith, and I have 15 years of experience working in marketing and advertisement. Throughout my career, I have helped companies increase their revenue by up to 50% using creative marketing strategies. Today, I am excited to share my insights in implementing effective social media campaigns.”
• Casual introduction: “Hey everyone, I’m John Doe, and I love hiking and playing the guitar in my free time. I’m really thrilled to talk to you about the impact of music on mental well-being, a topic close to my heart. Let’s dive right into it!”
• Creative introduction: “Imagine standing at the edge of a cliff, looking down at the breathtaking view of nature. That’s where my passion began for landscape photography. My name is Alex Brown, and I’ve been fortunate enough to turn my hobby into a successful career. Today, I’ll share my expertise on capturing stunning images with just a few simple techniques.”

Effective Templates for Self-Introductions

Part 9 name-role-achievements method template and examples.

When introducing yourself, consider using the NAME-ROLE-ACHIEVEMENTS template. Start with your name, then mention the role you’re in, and highlight key achievements or experiences you’d like to share.

“Hello, I’m [Your Name]. I’m currently working as a [Your Current Role/Position] with [Your Current Company/Organization]. Some of my key achievements or experiences include [Highlight 2-3 Achievements or Experiences].”

“Hello, I’m Sarah Johnson. I’m a Senior Software Engineer with over 10 years of experience in the tech industry. Some of my key achievements include leading a cross-functional team to develop a groundbreaking mobile app that garnered over 5 million downloads and receiving the ‘Tech Innovator of the Year’ award in 2020.”

“Hi there, my name is [Your Name]. I serve as a [Your Current Role] at [Your Current Workplace]. In my role, I’ve had the opportunity to [Describe What You Do]. One of my proudest achievements is [Highlight a Significant Achievement].”

“Hi there, my name is David Martinez. I currently serve as the Director of Marketing at XYZ Company. In my role, I’ve successfully executed several high-impact marketing campaigns, resulting in a 30% increase in brand visibility and a 15% boost in revenue last year.”

Template 3:

“Greetings, I’m [Your Name]. I hold the position of [Your Current Role] at [Your Current Company]. With [Number of Years] years of experience in [Your Industry], I’ve had the privilege of [Mention a Notable Experience].”

“Greetings, I’m Emily Anderson. I hold the position of Senior Marketing Manager at BrightStar Solutions. With over 8 years of experience in the technology and marketing industry, I’ve had the privilege of spearheading the launch of our flagship product, which led to a 40% increase in market share within just six months.”

Part 10 Past-Present-Future Method Template and Examples

Another template is the PAST-PRESENT-FUTURE method, where you talk about your past experiences, your current situation, and your future goals in a concise and engaging manner.

“In the past, I worked as a [Your Previous Role] where I [Briefly Describe Your Previous Role]. Currently, I am [Your Current Role] at [Your Current Workplace], where I [Briefly Describe Your Current Responsibilities]. Looking to the future, my goal is to [Your Future Aspirations].”

“In the past, I worked as a project manager at ABC Corporation, where I oversaw the successful delivery of multiple complex projects, each on time and within budget. Currently, I’m pursuing an MBA degree to enhance my business acumen and leadership skills. Looking to the future, my goal is to leverage my project management experience and MBA education to take on more strategic roles in the company and contribute to its long-term growth.”

“In my earlier career, I [Describe Your Past Career Experience]. Today, I’m [Your Current Role] at [Your Current Company], where I [Discuss Your Current Contributions]. As I look ahead, I’m excited to [Outline Your Future Plans and Aspirations].”

“In my previous role as a software developer, I had the opportunity to work on cutting-edge technologies, including AI and machine learning. Today, I’m a data scientist at XYZ Labs, where I analyze large datasets to extract valuable insights. In the future, I aspire to lead a team of data scientists and contribute to groundbreaking research in the field of artificial intelligence.”

“During my previous role as a [Your Previous Role], I [Discuss a Relevant Past Achievement or Experience]. Now, I am in the position of [Your Current Role] at [Your Current Company], focusing on [Describe Your Current Focus]. My vision for the future is to [Share Your Future Goals].”

“During my previous role as a Sales Associate at Maplewood Retail, I consistently exceeded monthly sales targets by fostering strong customer relationships and providing exceptional service. Now, I am in the position of Assistant Store Manager at Hillside Emporium, where I focus on optimizing store operations and training the sales team to deliver outstanding customer experiences. My vision for the future is to continue growing in the retail industry and eventually take on a leadership role in multi-store management.”

Examples of Self-introduction Emails

Part 11 job application self-introduction email example.

Subject: Introduction from [Your Name] – [Job Title] Application

Dear [Hiring Manager’s Name],

I am writing to introduce myself and express my interest in the [Job Title] position at [Company Name]. My name is [Your Name], and I am a [Your Profession] with [Number of Years] of experience in the field.

I am impressed with [Company Name]’s reputation for [Company’s Achievements or Mission]. I am confident that my skills and experience align with the requirements of the job, and I am excited about the opportunity to contribute to the company’s success.

Please find my resume attached for your review. I would appreciate the opportunity to discuss my qualifications further and learn more about the position. Thank you for considering my application.

Sincerely, [Your Name]

Related: Get More Interviews: Follow Up on Job Applications (Templates)

Part 12 Networking Event Self-Introduction Email Example

Subject: Introduction from [Your Name]

Dear [Recipient’s Name],

I hope this email finds you well. My name is [Your Name], and I am excited to introduce myself to you. I am currently working as a [Your Profession] and have been in the field for [Number of Years]. I am attending the [Networking Event Name] event next week and I am hoping to meet new people and expand my network.

I am interested in learning more about your work and experience in the industry. Would it be possible to schedule a quick call or meeting during the event to chat further?

Thank you for your time, and I look forward to hearing back from you.

Best regards, [Your Name]

Part 13 Conference Self-Introduction Email Example

Subject: Introduction from [Your Name] – [Conference or Event Name]

I am excited to introduce myself to you as a fellow attendee of [Conference or Event Name]. My name is [Your Name], and I am a [Your Profession or Industry].

I am looking forward to the conference and the opportunity to network with industry experts like yourself. I am particularly interested in [Conference or Event Topics], and I would love to discuss these topics further with you.

If you have some free time during the conference, would you be interested in meeting up for coffee or lunch? I would love to learn more about your experience and insights in the industry.

Part 14 Freelance Work Self-Introduction Email Example

Subject: Introduction from [Your Name] – Freelance Writer

Dear [Client’s Name],

My name is [Your Name], and I am a freelance writer with [Number of Years] of experience in the industry. I came across your website and was impressed by the quality of your content and the unique perspective you offer.

I am writing to introduce myself and express my interest in working with you on future projects. I specialize in [Your Writing Niche], and I believe my skills and experience would be a great fit for your content needs.

Please find my portfolio attached for your review. I would love to discuss your content needs further and explore how we can work together to achieve your goals. Thank you for your time, and I look forward to hearing from you soon.

Part 15 New Job or Position Self-Introduction Email Example

Subject: Introduction from [Your Name] – New [Job Title or Position]

Dear [Team or Department Name],

I am excited to introduce myself as the new [Job Title or Position] at [Company Name]. My name is [Your Name], and I am looking forward to working with all of you.

I have [Number of Years] of experience in the industry and have worked on [Your Achievements or Projects]. I am excited to bring my skills and experience to the team and contribute to the company’s success.

I would love to schedule some time to meet with each of you and learn more about your role in the company and how we can work together. Thank you for your time, and I look forward to meeting all of you soon.

Frequently Asked Questions

How can you create a powerful self-introduction script for job interviews.

To make a strong impression in job interviews, prepare a script that includes:

• Your name and current role or profession.
• Relevant past experiences and accomplishments.
• Personal skills or attributes relevant to the job.
• A brief mention of your motivation for applying.
• An engaging statement that connects your aspirations with the role or company.

How can students present a captivating self-introduction in class?

For an engaging self-introduction in class, consider mentioning:

• Your name and major.
• Where you’re from or something unique about your upbringing.
• Hobbies, interests, or extracurricular activities.
• An interesting fact or anecdote about yourself.
• Your academic or career goals and how they connect to the class.

What are tips for introducing yourself to a new team at work?

When introducing yourself to a new team at work, consider the following tips:

• Be friendly, respectful, and approachable.
• Start with your name and role, then briefly describe your responsibilities.
• Mention your background, skills, and relevant experiences.
• Share a personal interest or fun fact to add a personal touch.
• Express how excited you are to be part of the team and your desire to collaborate effectively.

How do you structure a self-introduction in English for various scenarios?

Regardless of the scenario, a well-structured self-introduction includes:

• Greeting and stating your name.
• Mentioning your role, profession, or status.
• Providing brief background information or relevant experiences.
• Sharing a personal touch or unique attribute.
• Concluding with an engaging statement, relevant to the context, that shows your enthusiasm or interest.
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• PowerPoint Templates

22 Best Free Introduce Yourself PowerPoint Templates

Self-introduction is something most people can’t avoid. When you join a new company or a new team, a wonderful self-introduction will often leave a deep impression on your colleagues and leaders, that’s why you must pay attention to this.

An Introduce Yourself PowerPoint slide will help you make a better presentation. Let’s take a look at some of the most amazing Introduce Yourself PowerPoint templates .

Table of Contents

Best introduce yourself powerpoint presentation slides free download, premium introduce yourself powerpoint template, one page about me slide templates, self introduction tips – 3 tips for making a good self introduction.

As one of the best PPT template collections, we have provided many free PowerPoint temples for you, what you need to do is download them from our site. Check here to download our free self-introduction PPT template .

1. Free Business Self Introduce Resume PowerPoint Template

Business Self Introduce Resume PowerPoint Template is a business presentation theme, it contains 10 unique slides and you can use this resume PowerPoint template to elevate your resume above other applicants.

This template is designed by  忘吃药的晓公子 (WeChat public number ID:CRAZYPPTer) and enjoy the ownership.

Table of contents:

• Cover slides
• About me slide: this is XIAO
• Work experience
• Career objective
• Thanks for watching

2. Yellow Resume Powerpoint Template – FREE DOWNLOAD

David Guetta is a stylish resume Powerpoint template that will help you impress your audience with ease. In this template, you will find slides to include your biography, skills, portfolio, education history, work experience, awards and diplomas, clients you’ve worked with, and contact information slides.

The free sample of this template consists of 15 unique slides, you need to purchase it to get the full package.

• Cover letter
• Experience work
• Social media

3. Kiddle Teacher CV Template

Kiddle Teacher CV is a free Google Slides theme and PowerPoint template. It has a creative and cute design and consists of 41 unique slides. Use this template to help you highlight your professional skills and get a new position as a teacher.

• interests/hobbies

4. Purple self introduction ppt template

Purple self-introduction ppt template is a minimalist presentation theme, it consists of 6 unique slides: about me, skill, education, portfolio, and contact me.

5. Minimalist Resume Template

Recruiters always look for candidates that stand out from the crowd. This visual presentation template is the best one that can help you stand out. Minimalist Resume consists of 14 different slides to impress your audience, click that “download” button and prepare to work!

6. Salesperson Self Introduce CV Template

This Self Introduce theme is designed for salespeople. it consists of 27 unique slides and has an abstract and minimalist design. Use this professional resume presentation template and get a new opportunity!

7. Modern CV Free PowerPoint Template Google Slides Theme

Do you want to surprise everyone with your resume? This modern CV PPT template will help you to create a professional self-introduction ppt. Download it now and use this PowerPoint template to create your own CV!

8. Free Cute Introduction PowerPoint Template

This cute PowerPoint template is made for creating a funny resume presentation. It comes with 7 unique slides with doodles and is compatible with PowerPoint, Keynote and Google Slides.

9. Free Portfolio Presentation PowerPoint Template

A minimalist-looking PowerPoint template that allows explaining different types of projects visually. It features all the necessary components to leave a long-lasting impression on the audience.

Main Features:

• eye-catching slides;
• modern fonts;
• modern color schemes.

Details | Download for Free in MonsterONE

10. Notebook Personal Profile PowerPoint Template

This free notebook -style PowerPoint template is made for crafting an attractive self-introduction presentation. It features 8 unique slides and is perfect for designers, and developers.

11. Student Part-Time Volunteer Resume Presentation (Canva)

This template is a creative and cute volunteer resume presentation template. It comes with 18 animated slides. It also has colorful 3D elements.

Note: this template is a Canva presentation template, you can customize it with Canva, or download it as a Google Slides or PowerPoint template .

12. Photo-centric Student Part-time Volunteer Resume Presentation (Canva)

This template is a beautiful photo-centric resume presentation template. It features 18 different slides with a well-organized structure.

13. Free Neumorphism CV Presentation Template

This is a Neumorphism design style CV/resume template designed for project managers. It features 12 unique & gorgeous slides.

14. Creative Resume Template

This free PowerPoint template is most suitable for making a business resume presentation. This template features 10 unique slides with a modern design.

15. Cute Self Introduction

If you are looking for a self introduction presentation for first day of class, check out this cute self introduction slide design! This template features 14 cute slides with pastel color and cute graphics, it will definitely catch your audience’s attention.

16. Retro Introducing Myself Presentation

With this colorful, scrapbook-style PowerPoint template, you’ll be able to create a more impactful school presentation. It includes 16 unique slides.

17. Free Teacher Resume Slides Template

This PowerPoint template was initially designed to present teacher resume but can be used for any education purpose. There are 16 unique slides included in this template.

18. Artist Portfolio Presentation

This Artist Portfolio Presentation template comes with a ultra-modern design and gray and purple color scheme, it offers 16 unique designs that will impress your audience.

19. Self Introduction Free PowerPoint (PPT) template

With 22 slides, and all the components needed to create a detailed portfolio presentation, this free ppt template is perfect for self introduction slideshow.

20. About Me Free PowerPoint (PPT) template

This free about me template comes with 20 slides, enough for creating most creative personal portfolio presentations. It has a creative and modern design.

21. All About Me Free PowerPoint (PPT) template

The All About Me PowerPoint template is an excellent choice for anyone looking for an attractive, ultra-modern presentation template. You can also download the Google Slides and Figma version if you need to.

22. Simple Resume Free PowerPoint (PPT) template

This free presentation template has a bold title and modern design. It’s an excellent choice for resume presentations. The template has 12 slides and is easy to edit and customize.

1. Neumorphism Self Introduction Resume CV PowerPoint Template

Neumorphism has become very popular in recent years, why not use it in your presentation? This Neumorphism PowerPoint template has a modern design, 25+ unique slides will meet all your needs.

2. Turner – CV Resume Portfolio PowerPoint Template (UI/UX Designer)

Turner is a professional CV resume PowerPoint template designed for UI/UX designers. It comes with 40+ modern slide designs including about me, education, portfolio, expertise, clients, contacts, and more.

3. Green Creative Resume PowerPoint Presentation Template

If you are looking for a creative self-introduction PowerPoint template, this template is perfect for you. This slide template has an attractive design with a light green color scheme, and the gradient background makes it look more beautiful.

• 6 Multipurpose Neumorphism PowerPoint Templates for You
• 11 Best Self Introduction PPT Templates To Create A Beautiful Presentation Slides in 2021
• 20 Best Top Free Modern CV Template (Word, PSD)

Many times you don’t need a complete self-introduction, a one-page about me slide is a better option to give a presentation about yourself in a business conference. The list below includes about me slide templates designed by experts. Explore them to spark more slideshow ideas.

Gradient Blue About me ppt template (2 slides)

A modern about me slide template for business presentation. It consists of photo, name, job position, skills, social media, and a brief introduction. There are two design layouts available in the template.

Free download

Simple About me slide (PowerPoint)

A minimalist about me PowerPoint slide template. This template will convey the most important message to your audience: who you are, what do you look like, and other information you need to convey to your audience.

Free Simple One-page Resume Template for PowerPoint

Use this free resume template to present your personal info, education, skill set, and work experience on a single page.

Dark One Page Self Introduction Portfolio (3 slides)

One page portfolio slide design with dark theme, 3 slides included.

One Page Self Introduction PPT Free Download (2 Layouts)

Bento grid style portfolio ppt template, 2 slides included.

• Tell your audience who you are!!! Tell your audience your name, what you do, keep it simple.
• Tell a story. No one likes an average experience, and stories are a great way to share your experiences.
• Ask for audience participation. Prepare some questions ahead of time that are ideally tailored to your audience’s experiences, interests, and knowledge.

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Home / Free Creative Google Slides & PowerPoint Templates / Free Creative Self Introduction PPT Template and Google Slides

Free Creative Self Introduction PPT Template and Google Slides

About the Template

Self introduction presentation template.

Want to introduce yourself in style? Then get this free creative self-introduction ppt template and Google slides and let your hiring manager know why to hire you.

Make a remarkable first impression with our Free Self-Introduction Presentation Template . Whether you’re introducing yourself in a presentation, clients, colleagues, or an online audience, this versatile and professionally designed template is your secret weapon.

Crafted with care and creativity, this professional self-introduction ppt template offers you a simple yet powerful way to showcase your personality, skills, and achievements. Engage your audience from the very beginning, leaving a lasting impact that sets you apart.

This introducing myself template comprises of 15 slides that will let you speak about yourself, your bio, work experience, skills, software skill, education, and many more topics in a catchy way. So, what you are waiting for is to get this self-introduction slide, get noticed by the recruiters, and exceed the chances of getting hired.

Land Your Dream Job – With Compelling Self Introduction

In today’s world, finding a job can be challenging, it can be due to excessive population or competitive job market. But remember, a strong first impression can be the difference between securing an interview and being overlooked.

By effectively communicating your skills, experiences in front of management, you can differentiate yourself from other candidates and increase your chances of success.

A powerful self-introduction isn’t stating your name and profession. It’s about how you impress the interviewers, leaving a lasting impression, and building rapport.

By effectively tailoring your introduction that highlights your most relevant qualifications, you can demonstrate your suitability for the role and inspire confidence in your abilities.

Creating a impressive about me presentation can be tricky, but with SlideChef’s self introduction slides, you can design a self-introduction that truly sets you apart, consider using our comprehensive template .

 By investing time in crafting a compelling self-introduction, you’ll be well on your way to achieving your career goals.

Features of this Self Introduction Template PPT

• Easy Customization: This self introduction slide offers easy customization, so you can easily customize the template to specific needs.
• Creative Slides: 15 creative slides to make your presentation look catchy
• Easily Compatible: Easily compatible with major presentation software like, Microsoft PowerPoint and Google slides
• Screen Option: 16:9 widescreen format best suited for all types of screens.

Use of this Free Self Introduction Slide Sample PPT

• Personal Branding:  Make yourself stand out and introduce yourself effectively in job interviews, networking events, or personal introductions with this creative self-introduction ppt template.
• Business Pitch:  Download this self-intro pt template and impress potential clients or investors by showcasing your skills and ideas in a clear and engaging manner.
• Educational Presentations:  Teachers and students can use it for self-introductions at the beginning of a school year or semester.
• Online Profiles:  Enhance your social media profiles or personal websites with a captivating introduction.
• Meetings and Workshops:  Start meetings, workshops, or webinars with a compelling self-introduction to engage your audience.

What you Will Find in this Self Introduction Presentation Slides

This comprehensive template offers a structured approach to effectively showcase your personal and professional background. It includes a variety of slides designed to highlight your key qualifications and achievements in a visually appealing and informative manner.

Here’s a breakdown of the slides included:

• About Me: A brief overview of your personality, interests, and professional goals.
• Biography: A detailed account of your life story, including childhood experiences, education, and key milestones.
• Work Experience: A chronological list of your past jobs, highlighting your responsibilities, achievements, and skills acquired.
• Skills: A comprehensive overview of your technical and soft skills, as well as any certifications or licenses.
• Certifications: A list of any professional certifications or licenses you hold.
• Work Process: A description of your approach to work, including your problem-solving skills, workflow, and methodologies.
• Portfolio: A collection of your best work, showcasing your skills and accomplishments.

Who Should Download this Creative Self Introduction PPT

This comprehensive about us template is designed to help individuals effectively highlight their skills, experiences, and personal brand. It’s a versatile tool that can be used for various professional and personal contexts.

Here Who Should Get this Self Introduction Sample PPT

• Job seekers: Use this introduction template to create a compelling resume or CV, highlighting your qualifications and accomplishments.
• Students: Showcase your academic achievements, extracurricular activities, and career aspirations.
• Freelancers and entrepreneurs: Promote your services and expertise to potential clients.
• Networkers: Leave a lasting impression at industry events and conferences by sharing your professional profile.
• Job applicants: Prepare for interviews by providing a structured overview of your background and qualifications.
• Career changers: Transition smoothly into a new field by demonstrating your transferable skills and experiences.
• Work Preview: A brief overview of your current or most recent project, highlighting your contributions and outcomes.
• References: A list of references who can attest to your skills and qualifications.
• Thank You: A closing slide expressing your gratitude for the opportunity to present your self-introduction.

By crafting a super-impressive about me template, you can position yourself as a confident, qualified, and memorable candidate . Remember to tailor your introduction to the specific context and highlight your most relevant qualifications.

Ready to make a lasting impression? Download our comprehensive self-introduction template today and start building your professional narrative.

Looking to unlock your full potential? Our self-development templates library offers a wide range of resources to help you achieve your personal and professional goals. From productivity techniques to mindfulness practices, we have something for everyone. Explore our collection of templates, guides, and articles to discover the tools you need to thrive.

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How to Introduce Yourself Before Starting a Presentation

Introducing yourself can be nerve-wracking, especially in a foreign language. Whether it’s for a presentation, email, cover letter, or casual setting, knowing how to introduce yourself effectively can leave a lasting impression. In this post, we’ll break down different approaches to self-introductions, from formal to informal, and offer examples to help you tailor your introduction to any situation. Let’s get started!

1. How to Introduce Yourself in a Presentation

When introducing yourself in a presentation, it’s essential to cover specific key elements that help set expectations and engage your audience. Here’s a step-by-step breakdown of what to include in a professional, yet approachable, presentation introduction:

• Greeting : Start with a polite greeting to establish a connection with your audience.
• Name and Affiliation : Clearly state your name and professional background. This provides the audience with context about your expertise or authority on the topic.
• Purpose of the Presentation : Briefly outline the main purpose of your talk so the audience knows what to expect.
• Overview of Content : Provide a brief snapshot of the key points or sections you will cover. This gives your audience a roadmap of what’s ahead.
• Engagement Invitation : Invite your audience to ask questions or participate, indicating whether you’d prefer questions during or after the presentation.
• Acknowledgments : If relevant, express gratitude to the organizers or contributors to your presentation.

“Good morning, and thank you all for joining me today. My name is Hana Jung, and today I’ll be talking about new solar panels for homes. We’ll explore how they work, their benefits, and why they’re a sustainable choice for cities. I encourage your questions and comments but kindly ask that we save them for the Q&A session at the end. Lastly, I’d like to express my gratitude to the GreenTech Conference organizers for inviting me and to my team back in Seoul for their continuous support.”

2. Creative Self-Introduction

A creative self-introduction can make you memorable, especially in a casual or networking scenario. Here are some tips for introducing yourself creatively:

• Start with a Spark : Open with something surprising, humorous, or attention-grabbing.
• Use Storytelling : Share a short story about yourself that illustrates who you are in an engaging way.
• Connect the Dots : Relate your story or facts to the context of your introduction to make it relevant.
• Finish with an Invitation : Encourage further engagement by asking a question or leaving a thought-provoking comment.

“Hi, I’m Maya. My journey has taken me from the mountain highs of Nepal to the heart of tech startups in Silicon Valley, where every website I create tells a unique story. What’s your story? I’d love to help share it with the world.”

3. Informal Self-Introduction

For more casual settings, like meeting new friends or attending social events, you’ll want to keep your introduction light and conversational. Here’s how to introduce yourself informally:

• Keep It Simple : Use a friendly greeting followed by your name.
• Personal Touch : Share a bit about your hobbies or interests.
• Engage : Ask a question to invite the other person to share something about themselves.

“Hey there, I’m Alex! I’m a huge fan of jazz music and love hiking on weekends. What kind of things are you into?”

4. Self-Introduction in Emails

In professional settings, emails often serve as the first impression. Crafting a clear, concise, and engaging self-introduction in an email can help build rapport quickly. Here’s how to structure it:

• Greeting : Open with a polite greeting appropriate for the time of day.
• Name and Position : Introduce yourself by stating your name and your role.
• Purpose : Mention why you’re writing and briefly touch on your background or skills.
• Call to Action : Express a desire to collaborate or offer help if needed.
• Sign-Off : End with a professional closing and your full name.

Subject : Introduction – Alex Martin, Your New Marketing Coordinator

Hello Team,

Good [morning/afternoon],

My name is Alex Martin, the new Marketing Coordinator working under Jasmine Lee, the Marketing Director. I am excited to be a part of this fantastic team and look forward to contributing to our projects and goals. My background is in digital advertising, and I’m passionate about developing creative marketing strategies.

Feel free to reach out if there’s anything you’d like to discuss. I’m eager to get to know all of you and begin collaborating!

Warm regards, Alex Martin

5. Writing a Self-Introduction for a Cover Letter

A cover letter is your first chance to make a strong impression when applying for a job. Here’s how to introduce yourself in a cover letter:

• Salutation : Begin with a formal greeting, preferably addressing the hiring manager by name.
• Mention the Job Title : State the position you’re applying for and where you found the listing.
• Professional Background : Share a brief summary of your relevant experience and qualifications.
• Show Enthusiasm : Express why you’re excited about the opportunity and how your skills align with the company’s values.
• Closing Statement : Politely conclude by thanking the hiring manager and expressing your interest in further discussions.

Dear Hiring Manager,

I am writing to express my interest in the Graphic Designer position at Creative Studios, as advertised on LinkedIn. With a Bachelor’s degree in Visual Arts and three years of experience in a busy marketing agency, I have developed a strong skill set in design that aligns perfectly with your team’s needs.

Your commitment to innovative design inspires me, and I am eager to contribute to your company’s success. My previous role involved collaborating on projects that won industry awards, and I look forward to bringing my creativity and passion for design to your organization.

Thank you for considering my application. I hope to discuss how my skills and ideas can contribute to Creative Studios’ future success.

Best regards, Jamie Smith

6. Professional Network Introduction (LinkedIn)

When introducing yourself on a professional network like LinkedIn, keep it short but impactful. Here’s how to write a compelling introduction:

• Start with a Friendly Greeting : Keep the tone polite and professional.
• Share Your Current Role : Mention your job or area of expertise.
• Express Interest : Highlight what you admire about the person or company you’re reaching out to.
• Call to Action : Invite the person to connect or share insights.

Dear Mr. Thompson,

I’m Alex Martinez, a marketing specialist passionate about digital innovation and brand strategy. I’ve followed your posts on marketing trends, and I’m impressed by your impactful strategies at Thompson Marketing Inc. As someone who is committed to continuous learning in the field, I would be grateful to connect and share insights.

Warm regards, Alex Martinez

7. Final Thoughts on Self-Introductions

Whether in professional settings or social situations, having a polished and adaptable self-introduction in English is key to making strong first impressions. By tailoring your self-introduction to the context and audience, you’ll communicate confidently and engage others from the very beginning.

Don’t get caught unprepared! Take some time to practice writing and speaking different versions of your self-introduction for various scenarios. With a little preparation, you’ll master the art of introducing yourself in English in no time.

If you have any questions or need help with your self-introduction, feel free to drop a comment below!

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Measuring Dimensions of Self-Presentation in Twitter Bios and their Links to Misinformation Sharing

Social media platforms provide users with a profile description field, commonly known as a “bio,” where they can present themselves to the world. A growing literature shows that text in these bios can improve our understanding of online self-presentation and behavior, but existing work relies exclusively on keyword-based approaches to do so. We here propose and evaluate a suite of simple, effective, and theoretically motivated approaches to embed bios in spaces that capture salient dimensions of social meaning, such as age and partisanship. We evaluate our methods on four tasks, showing that the strongest one out-performs several practical baselines. We then show the utility of our method in helping understand associations between self-presentation and the sharing of URLs from low-quality news sites on Twitter , with a particular focus on explore the interactions between age and partisanship, and exploring the effects of self-presentations of religiosity . Our work provides new tools to help computational social scientists make use of information in bios, and provides new insights into how misinformation sharing may be perceived on Twitter.

Introduction

On social media sites like Tumblr (Yoder et al. 2020 ) , Twitter (Li et al. 2020 ; Rogers and Jones 2021 ; Pathak, Madani, and Joseph 2021 ) , TikTok (Darvin 2022 ) , and Parler (Bär, Pröllochs, and Feuerriegel 2023a ) , the profile description field (or bio ) asks users to describe themselves in a single text box. Users commonly do so with a combination of delimited phrases, each of which can range from unigrams like “Republican” to more complex expressions like “2020 Election Truth Seeker” (Pathak, Madani, and Joseph 2021 ) .

In most social settings, people aim to present to others only a single social identity (MacKinnon and Heise 2010 ; Schröder, Hoey, and Rogers 2016 ) . Examples of identities include social roles, like “doctor” and “mother”, group memberships like “Democrat” and “Yankees fan”, and social categories like “black people” and “women” (Tajfel and Turner 1979 ) . Bios thus present a unique setting where we can observe individuals explicitly labeling themselves with multiple social identities (Marwick and boyd 2011 ) . 1 1 1 Bios really express phrases that signal identity , what Pathak, Madani, and Joseph ( 2021 ) call personal identifiers . Here, we retain the phrase (social) identity as a familiar and concise shorthand. With respect to the language of self-presentation (Johnstone 1996 ) , bios are therefore an important tool for social scientists for three reasons.

First, bios provide insight into patterns of shared identity. For example, bios have been used to show that people who label themselves coffee snobs tend to be the same that label themselves marketing gurus (Pathak, Madani, and Joseph 2021 ) . They have also been used to better understand the increasing entanglement of partisanship and culture in social identities in the United States (Essig and DellaPosta 2024 ; Phillips, Carley, and Joseph 2024 ) . Second, bios allow us to study links between the identities people select for themselves and behavior. Users’ choices on how to label themselves can be linked to, for example, decisions on who chooses to re-blog whom on Tumblr (Yoder et al. 2020 ) , or how people respond to marketing campaigns (Ng and Cruickshank 2023 ) . Finally, bios can help us identify people who share a certain characteristic. To this end, p rior work has also explored how bios can help identify individuals such as Qanon supporters (Bär, Pröllochs, and Feuerriegel 2023a ) and journalists (Zeng et al. 2019 ) , characterize the demographics associated with the self-presentation of particular identities (Pathak, Madani, and Joseph 2021 ) , and even reflect current social movements (Rogers and Jones 2021 ; Hare and Jones 2023 ) .

Existing quantitative work on bios has, however, has focused almost exclusively on characterizing bios via the presence of particular phrases, whether through dictionary-based methods ( Rogers and Jones 2021 ; Zeng et al. 2019 ; Bär, Pröllochs, and Feuerriegel 2023b ) or through analysis of patterns in phrases extracted with regular expressions ( Yoder et al. 2020 ; Pathak, Madani, and Joseph 2021 ; Essig and DellaPosta 2024 ; Ng and Cruickshank 2023 ) . While findings from these approaches can be illuminating, they also make it difficult to study how bios align with particular dimensions of importance to social scientists, such as partisanship (Kozlowski, Taddy, and Evans 2019 ) . Acknowledging these challenges and opportunties, Jiang, Ren, and Ferrara ( 2023 ) develop an approach that uses modern NLP methods to infer ideological leanings implied by bios. However, their work focuses only on learning political ideology and also requires data beyond the bio itself to perform estimation. There thus exists a need for a method that can help us to measure self-presentation in bios in ways that 1) let us move beyond keyword-based methods and 2) beyond political ideology, 3) without requiring additional data.

To this end, the goals of this paper are two-fold. The first goal of the present work is to develop and evaluate three methods to project English-language social media bios onto multiple dimensions of social meaning, without retraining a new embedding model for each new desired dimension . Our methods are technically straightforward, in that we extend existing work on how to scale text along dimensions of meaning like gender and race using projections of text embeddings (Wilkerson and Casas 2017 ) . However, we build on this work by developing approaches specifically for the study of social media bios. Our models are grounded in the relevant social science , in that each method we present draws on social identity theory (Tajfel and Turner 1979 ) to learn bio embeddings by making use of the fact that many bios consist of multiple, clearly delimited social identities (Marwick and boyd 2011 ; Pathak, Madani, and Joseph 2021 ) . As such, unlike in standard embedding models where we aim to embed words that mean the same thing closely together, our models aim to create embedding spaces (and projections of them) where phrases that are applied to the same people are close together in embedding space.

After describing our three approaches, we present an extensive validation across four tasks: 1) predicting which identities will appear in the same bio, 2) how projections of embeddings for specific identities within bios onto dimensions of age, gender, and partisanship correlate with human judgements, 3) whether projections using the embeddings of entire bios also correlate with human judgements, and 4) whether projections using the embeddings of entire bios correlate with other measures of user ideology, and show similar associations to behavior . Across all evaluation tasks, we find that the most effective model is an SBERT (Reimers and Gurevych 2019 ) model fine-tuned on bios . In Evaluation 1), we show that this model is best able to make predictions about identities the model has not seen, emphasizing its ability to generalize to new and unseen identities. Evaluations 2) and 3) show that this model effectively captures perceptions of how individuals present themselves, which is critical for understanding how other users interpret a particular bio (Heise 1987 ; Pathak, Madani, and Joseph 2021 ) . Finally, while our focus is on what is implied to others when a user self-presents, rather than inferring some “truth” about a user , we show that estimates of user ideology by our method correlate with other known approaches for doing so. Moreover, we show that associations with behavioral patterns (of misinformation sharing) using our method are consistent with other approaches.

Having identified a single model to embed bios, we continue to the second goal of our work, which is to explore associations between self-presentation in bios and the rate of low- (relative to high-) quality news shares on Twitter . Specifically, we focus on two research questions that have not been addressed in the existing literature. First, perhaps the most well-established finding in this literature is that misinformation sharing is more prevalent among older, right-leaning individuals (Grinberg et al. 2019 ; Guess, Nagler, and Tucker 2019 ; Brashier and Schacter 2020 ; Osmundsen et al. 2021 ; Nikolov, Flammini, and Menczer 2021 ) . However, due in part to sample size restrictions, existing work has theorized (Grinberg et al. 2019 ) but not tested empirically the existence of an interaction between age and partisanship. In the present work, using two different large datasets of Twitter users, we indeed show for the first time that such an interaction effect exists between self-presentation of age and partisanship, in that self-presenting as older and Republican has a multiplicative association with misinformation sharing. Second, while scholars have suggested that religiosity is a critical dimensions of the self associated with misinformation sharing online, no empirical work has addressed this point (Druckman et al. 2021 ) . To this end, we present 1) new and convincing evidence that on average, presenting as more religious is strongly associated with misinformation sharing.

In sum, the present work provides three contributions:

We propose, evaluate, and make public 2 2 2 The model is publicly available for use on https://github.com/navidmdn/identity˙embedding . a simple, effective, and theoretically motivated tool to embed English-language bios in socially meaningful latent spaces.

We show that our method 1) can be used to project both individual social identities and entire social media bios onto salient dimensions of social meaning, such as partisanship, gender, and age in ways that correlate with human judgements in two new survey datasets, and 2) correlates well with other measures of user ideology .

We use our model to extend our understanding of the relationship between how active news-sharing accounts on Twitter self-present and the proportion of news they share coming from low-quality news sites, particularly with respect to interactions between age and partisanship, and with respect to religiosity .

Measuring text on social dimensions of meaning

Social psychologists have developed a host of survey-based methods to measure associations between social identities and dimensions of social meaning. This estimation of identities on such dimensions is a core focus of social psychologists (Schröder, Hoey, and Rogers 2016 ; Fiske et al. 2002 ) , because connecting self-presentation along specific dimensions of social relevance to social behavior is important for developing and testing new theories (MacKinnon and Heise 2010 ) . Below, we leverage these established approaches to evaluate our methodology. However, survey data do not scale to the myriad ways people identify themselves (MacKinnon and Heise 2010 ) , are usually too small to capture differences across subgroups or contexts (Smith-Lovin and Douglas 1992 ) , and struggle to account for linguistically complex identities or situations where multiple identities are applied (Joseph and Morgan 2021 ) .

Most of the computational tools developed to address these challenges function by projecting embeddings from distributional semantic models ( DSM ), such as BERT, onto particular dimensions of meaning. The present work is most aligned with efforts that use contextualized embeddings (e.g. Kurita et al. 2019 ; Lucy, Tadimeti, and Bamman 2022 ; Field, Bhat, and Tsvetkov 2019 ) to do so. However, we expand on these methods in that we aim to focus not on linguistic similarity , but rather similarity in the types of people who use particular identities . More specifically, DSMs are based on the assumption that contextual similarity—similarity in where phrases appear in text—is a strong proxy for semantic similarity (roughly, synonomy). The idea behind this assumption is that phrases with high semantic similarity should have similar cognitive associations to other phrases, and thus high contextual similarity too (Miller and Charles 1991 ) . While deeply intertwined (Caliskan and Lewis 2020 ) , these linguistic associations and the socio-cultural associations of interest to us differ. Linguistic associations represent phrases with similar associations to similar other phrases ; what we desire are phrases with similar associations to similar kinds of people . While methodologically consistent with prior work, then, our work extends the existing literature by defining a different socio-theoretic goal that is consistent with the existing literature on self-presentation. We also provide several new evaluation datasets for future work.

In focusing on sets of identities applied to individuals, our work also relates to entity-centric text analysis (Field and Tsvetkov 2019 ) . Entity-centric work focuses on using phrases with known meanings (e.g. from surveys) to understand the portrayal of individuals (Antoniak, Mimno, and Levy 2019 ; Mendelsohn, Tsvetkov, and Jurafsky 2020 ) . Our method builds on a complementary idea, namely that we can use the fact that all identities in a bio refer to a single entity (a user) to create better embeddings. Similar in this vein is the work of Bamman and Smith ( 2014 ) , who use this idea to infer character personas in literature. The present work compliments these efforts by using entity-centric data to produce embeddings, rather than phrase clusters.

Our work also ties to the literature that explores the language associated with how people express misinformation (Mu and Aletras 2020 ; Shu et al. 2017 ; Rashkin et al. 2017 ) . More specifically, we complement these efforts to study how people express specific instances of misinformation by exploring how people who tend to spread misinformation present themselves via particular (sets of) social identities.

The Demographics (and Self-presentations) of Misinformation Sharing

The study of misinformation online has exploded in recent years (Lazer et al. 2018 ) . Within this literature, several papers have looked at associations between demographics and rates of misinformation sharing. Typically, they do so by gathering demographics either via survey (e.g. Grinberg et al. 2019 ) or using voter records (Guess, Nagler, and Tucker 2019 ; Mosleh, Pennycook, and Rand 2020 ) , and then associating contained demographic information with rates of misinformation sharing. Across studies, however, prior work has repeatedly found that the best predictors of misinformation exposure and sharing online are 1) old age (Brashier and Schacter 2020 ) , 2) alignment with the political right (Osmundsen et al. 2021 ; Nikolov, Flammini, and Menczer 2021 ) , and 3) overall levels of online activity (Grinberg et al. 2019 ) .

Our work compliments these existing efforts in a number of ways. First, these prior works tend to use small-N samples of misinformation sharers because of the challenges and biases associated with their recruitment methods (Hughes et al. 2021 ) . For example, Grinberg et al. ( 2019 ) and Guess, Nagler, and Tucker ( 2019 ) , analyze sharing patterns in settings where only 400 Twitter users and 101 Facebook users shared any misinformation, respectively. In contrast, we analyze two different and much larger datasets; in the larger one, 77,190 accounts share at least one low-quality news link.

Second, we focus here on demographics conveyed through self-presentation . These self-presented demographics are important in their own right for understanding who other Twitter users perceive to be sharing misinformation, perceptions that do not always align with a user’s “true demographics” (Nguyen et al. 2014 ) . Critically, then, we do not claim that our method infers demographics of users, nor do we believe it does so. Indeed, these self-presentations may vary from demographics in at least two ways. First, individuals may consciously choose not to convey certain demographic information online, such as gender (Buss, Le, and Haimson 2022 ) , and more generally choose which dimensions of the self are most important to present to their Twitter audience (Marwick and boyd 2011 ) . Second, non-human accounts, such as those run by Russia’s Internet Research Agency (IRA), may fabricate self-presentations to shape online discussion (Zhang et al. 2021 ) . Prior studies that link users to surveys or voter records rule out these latter accounts in their sampling approach. In contrast, we aim to focus on which dimensions of social meaning are salient, or cast as salient, by those sharing misinformation unknowingly or for manipulation. We thus study here how the misinformation shares present their identity .

These two distinctions shape the two novel research questions we study here. First, the larger size of our dataset lets us explore interactions between self-presentations of age and partisanship, as compared to prior work which analyzes only the main effects. Second, our focus on dimensions of self-presentation instead of traditional demographics lets us analyze a novel, although well-theorized (Druckman et al. 2021 ) , empirical question: how is (self-presented) religiosity associated with misinformation sharing?

Methods for Embedding Twitter Bios

We propose three models that leverage existing methods to project phrases onto dimensions of social meaning in different ways. Our first model uses data only from bios, whereas the latter two use fine-tuning to balance between meanings in bios and semantic information in large, pre-trained DSMs. In all cases, our models are trained by using patterns in the multiple identities that appear in many social media bios. Because of this, it is useful to introduce some limited notation. First, let X 𝑋 X italic_X denote a dataset of bios where identities have been extracted, e.g. by using a regular expression (Yoder et al. 2020 ; Pathak, Madani, and Joseph 2021 ) . We assume X i = { x 1 i , x 2 i , … , x k i } superscript 𝑋 𝑖 subscript superscript 𝑥 𝑖 1 subscript superscript 𝑥 𝑖 2 … subscript superscript 𝑥 𝑖 𝑘 X^{i}=\{x^{i}_{1},x^{i}_{2},...,x^{i}_{k}\} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT = { italic_x start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT , italic_x start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT , … , italic_x start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT } represents a set of k 𝑘 k italic_k identities extracted from a single bio, and that V 𝑉 V italic_V is a vocabulary of all unique identities in the training portion of X 𝑋 X italic_X .

Bio-only model

Our Bio-only model is constructed by applying word2vec (Mikolov et al. 2013 ) to X 𝑋 X italic_X . In common terminology for word2vec , we treat identities as words and bios as a context. Our intuition is that if the word2vec model can leverage contextual similarity on the “word-to-linguistic context” matrix to identify words with shared semantic meanings, it may also be useful to leverage the “identity-to-person context” matrix to identify phrases with shared socio-cultural meanings. We use word2vec models with an embedding size of 768 to match the embedding size of the other models used below, and train for 300 epochs with a window size of 8 (only .01% of bios in our training data contain more than 8 identities). Additional minor details are provided in the appendix.

Fine-tuned BERT

To fine-tune BERT, we use a masked language modeling (MLM) objective, randomly masking one of the identities in each bio. To prepare our dataset for training, we take each of the instances X i superscript 𝑋 𝑖 X^{i} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT and concatenate the phrases in it to form a full sentence. We then mask one of the identities and fine-tune a BERT-base model for 5 epochs while monitoring 10% of the training set as validation data. We used a learning rate of 2e-5 with a batch size of 64. Model training took approximately one day using a single A100 GPU. When bios are shorter than the context window size, padding is added; attention masking is used to ensure padding does not impact the embedding. We keep the embedding size of the BERT model at the default 768.

Fine-tuned SBERT

Finally, we construct a final model by fine-tuning Sentence-BERT (Reimers and Gurevych 2019 ) . Sentence-BERT uses contrastive learning , where the learning setup must be carefully constructed (Schroff, Kalenichenko, and Philbin 2015 ) . We develop an intuitive but effective approach here based on shared identities. In a contrastive learning framework, each data point is a triplet consisting of an anchor , a positive , and a negative sample. Our goal is to reshape the embedding space through fine-tuning such that for each triplet, the distance between anchor and positive samples, which co-occur within a bio in our setup, is minimized while the distance between anchor and negative samples, which do not, is maximized. As above, padding and attention masks are used when bios are shorter than the size of the context window. The embedding size of our selected sentence BERT model is 768 which matches the embedding size of all other proposed approaches for fair comparison.

We can frame this contrastive learning problem as a regression task: given a triplet of anchor ( X a subscript 𝑋 𝑎 X_{a} italic_X start_POSTSUBSCRIPT italic_a end_POSTSUBSCRIPT ), positive ( X p subscript 𝑋 𝑝 X_{p} italic_X start_POSTSUBSCRIPT italic_p end_POSTSUBSCRIPT ) and negative ( X n subscript 𝑋 𝑛 X_{n} italic_X start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT ) samples and a similarity measure (here, cosine), our objective is for c ⁢ s ⁢ ( X a , X p ) = 1.0 𝑐 𝑠 subscript 𝑋 𝑎 subscript 𝑋 𝑝 1.0 cs(X_{a},X_{p})=1.0 italic_c italic_s ( italic_X start_POSTSUBSCRIPT italic_a end_POSTSUBSCRIPT , italic_X start_POSTSUBSCRIPT italic_p end_POSTSUBSCRIPT ) = 1.0 and c ⁢ s ⁢ ( X a , X n ) = 0.0 𝑐 𝑠 subscript 𝑋 𝑎 subscript 𝑋 𝑛 0.0 cs(X_{a},X_{n})=0.0 italic_c italic_s ( italic_X start_POSTSUBSCRIPT italic_a end_POSTSUBSCRIPT , italic_X start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT ) = 0.0 for all training points, where c ⁢ s 𝑐 𝑠 cs italic_c italic_s stands for cosine similarity. We can then optimize this objective using mean squared error. The challenge is to construct an effective set of triplets to train on. To do so, we first take a bio X i superscript 𝑋 𝑖 X^{i} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT from the training set, and then randomly select an identity from X i superscript 𝑋 𝑖 X^{i} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT to be the positive sample. We name the remaining identities in X i superscript 𝑋 𝑖 X^{i} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT the anchor sample. Finally, we randomly select an identity that never co-occurs with the positive sample as the negative sample. As an example, from the bio [assistant professor, Bernie supporter, #blacklivesmatter] we set assistant professor, #blacklivesmatter as the anchor sample, Bernie supporter as the positive sample, and randomly select a negative sample that never co-occurred with Bernie supporter . We construct a triplet for each X i ∈ X superscript 𝑋 𝑖 𝑋 X^{i}\in X italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT ∈ italic_X using this method, and use these to fine-tune an mpnet-base Sentence-Bert model. Models were trained for 5 epochs for one day on a single A100 GPU.

Training Data

All models are trained on a sample of 3,534,903 bios from users who sent an English-language tweet captured in the Twitter Decahose 3 3 3 A sample of approximately 10% of all tweets. in 2020. We use the method from Pathak, Madani, and Joseph ( 2021 ) to extract identities from bios. Their extraction method consists of two steps, one where bios are split into chunks using a manually crafted regular expression, and a second cleaning step. For example, from the Twitter bio “Progressive Christian, wife, I am a proud Canadian,” their method extracts Progressive Christian , wife and proud Canadian . Given that our models learn from patterns in shared identity, we use only bios that contain at least two identities for training, with | V | 𝑉 |V| | italic_V | =22,516. A complete description of the dataset is available in the appendix.

We conduct four evaluations to assess model validity. The first is a prediction task, where we evaluate the full embedding space of each model and its ability to capture information that shapes users’ decisions on which sets of identities to place in their bio. The second connects our work to the existing literature on embedding and projecting individual social identities onto dimensions of social meaning. The third assesses our ability to project entire bios onto meaningful dimensions, with an eye towards validating our approach for our case study. Finally, the fourth task shows that our measures of partisanship correlate with other existing measures, and that our methods are associated with the behavior of interest (misinformation sharing) in the same way. Here, we describe each task and results for it in four separate subsections.

Can we Predict Held-out Identities?

Task description.

To perform this evaluation, we randomly sample another 1.5M Twitter bios from the Decahose using the same approach as above, creating an 80/20 train/test split between the two samples. For each observation in the test set, we ensure that at least one of the identities is in V 𝑉 V italic_V (which is defined using the training data). For the i 𝑖 i italic_i th sample, we then take one identity, X t i subscript superscript 𝑋 𝑖 𝑡 X^{i}_{t} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT , as the hold-out target and call the rest of the bio X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT . We ensure X t i subscript superscript 𝑋 𝑖 𝑡 X^{i}_{t} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT is in V 𝑉 V italic_V , i.e. in all cases the target is observed at least once in the training data. This task notably favors the three new models we present here, in that they are each trained in a manner similar to the prediction task. However, the comparison is still useful to 1) ensure that fine-tuning works as expected and 2) to compare between the three new models. With respect to the latter point, there is reason to believe that the word2vec model should outperform the Fine-tuned BERT or fine-tuned SBERT model, because the word2vec model is trained only on in-domain data relevant to the task.

To generate predictions, we first generate an embedding for X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT , L r i = e ⁢ m ⁢ b ⁢ e ⁢ d ⁢ d ⁢ i ⁢ n ⁢ g ⁢ ( X r i ) subscript superscript 𝐿 𝑖 𝑟 𝑒 𝑚 𝑏 𝑒 𝑑 𝑑 𝑖 𝑛 𝑔 subscript superscript 𝑋 𝑖 𝑟 L^{i}_{r}=embedding(X^{i}_{r}) italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT = italic_e italic_m italic_b italic_e italic_d italic_d italic_i italic_n italic_g ( italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT ) 4 4 4 Extended details on how embeddings are generated for each model are in the Appendix. . We then measure the cosine similarity of L r i subscript superscript 𝐿 𝑖 𝑟 L^{i}_{r} italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT with the embedding of all identities v ∈ V 𝑣 𝑉 v\in V italic_v ∈ italic_V , S ⁢ i ⁢ m ⁢ i ⁢ l ⁢ a ⁢ r ⁢ i ⁢ t ⁢ y ⁢ ( L r i , L v i ) 𝑆 𝑖 𝑚 𝑖 𝑙 𝑎 𝑟 𝑖 𝑡 𝑦 subscript superscript 𝐿 𝑖 𝑟 subscript superscript 𝐿 𝑖 𝑣 Similarity(L^{i}_{r},L^{i}_{v}) italic_S italic_i italic_m italic_i italic_l italic_a italic_r italic_i italic_t italic_y ( italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT , italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_v end_POSTSUBSCRIPT ) , leaving us with | V | 𝑉 |V| | italic_V | similarity scores to L r i subscript superscript 𝐿 𝑖 𝑟 L^{i}_{r} italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT .We evaluate similarity scores returned by each model using two evaluation metrics: average rank and log softmax score . Average rank is computed by, for each test point, finding the ranking of X t i subscript superscript 𝑋 𝑖 𝑡 X^{i}_{t} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT in the scores produced by each model, and taking the average over all test points. The log softmax score draws on prior work (Joseph and Morgan 2021 ) and transforms similarity scores into a probability distribution using the softmax, and then takes the log of the result for X t i subscript superscript 𝑋 𝑖 𝑡 X^{i}_{t} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT .

Finally, for evaluating the out-of-domain generalizability of our models, i.e. how well the model generalizes to unseen identities, we split our test data into two sets, a Main Evaluation set, where X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT also contains at least one identity observed in the training data, and a Generalizability set, in which no identities in X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT are seen in the training data. This is necessary to fairly evaluate our Bio-only model , which has a restricted vocabulary and does not generalize to out-of-domain phrases, to the other models, each of which are capable of handling out-of-domain text. 5 5 5 Note that X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT can still contain phrases that the Bio-only model does not recognize and replaces them with the 0-vector. It is also a useful test of the (in-domain) generalizability of the other models. We evaluate results separately for these two test datasets.

We compare our models to three baseline DSMs used frequently in prior work: BERT (Devlin et al. 2019 ) , RoBERTa (Liu et al. 2019 ) , and Sentence-BERT (Reimers and Gurevych 2019 ) (see appendix for details) . As in much of the prior work (Lucy, Tadimeti, and Bamman 2022 ) , these approaches are not fine-tuned on bios, giving a baseline for how important in-domain training is for our problem.

In contrast to our expectations, the Fine-tuned SBERT model consistently outperforms all other models on both evaluation metrics on the Main Test set. Figure  1 shows this, and also reveals that the next best model, in all cases, was the Bio-only model , and that the Fine-tuned BERT model does not show the same jump in performance relative to the baseline BERT model that the Fine-tuned SBERT model does. Finally, we see that the baseline SBERT model outperforms the baseline BERT model.

The fact that the fine-tuned SBERT model improves over the Bio-only model, but the Fine-tuned BERT model does not, is evidence that knowledge from the pre-trained SBERT model (but not BERT) is useful in our setting. It also shows that performance gains cannot only be attributed to fine-tuning on in-domain language, but instead that our contrastive learning setup was effective and that Sentence-BERT is indeed the more effective initial model for fine-tuning, at least on this evaluation task. The second column of Figure  1 shows that the Fine-tuned SBERT model also performs best on the Generalizability test set. Even when the Fine-tuned model is not exposed to any of the identities in X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT , it improves by nearly 100% over the standard SBERT model in terms of average rank. Figure  1 also makes clear that there is room for improvement. To this end, we conduct an error analysis ; see the appendix for details.

Do Projections of Single Identities Correlate with Human Judgements?

Following prior work (Joseph and Morgan 2020 ) , we assess how well our embeddings can be used to project identities onto dimensions of social meaning in ways that correlate with human judgements. As no prior work focuses on identities that are common in bios, however, we construct a novel survey dataset for this task. We provide brief details on the study here, full details can be found in the Appendix.

We asked 140 respondents on Prolific to rate 250 common identities in Twitter bios on three widely studied dimensions: gender, age, and partisanship. We use the mean of ratings for each identity on each dimension in our analysis. To select identities, we ranked identities in the Twitter dataset by frequency, and then manually selected the first 250 phrases that clearly signaled identity. For each identity on each dimension, respondents were asked to move a slider to represent their perception of where people who label themselves as that identity were likely to fall. For partisanship, for example, the slider ranged from “Always [a] Democrat” to “Always [a] Republican.” Figure  2 provides an example question. For gender and age, we followed the approach outlined by Joseph and Morgan ( 2020 ) exactly, using the same slider. Specifically, for age, participants were asked to rate identities on perceived age from 0-100, for gender, the question appears as in Figure  2 , replacing “Republican” with “Man” and “Democrat” with “Woman.”

To construct projections for each embedding model, for each identity, onto these dimensions, we follow the literature and 1) embed identities as defined above, 2) define a set of words and phrases that denotatively characterize each “end” of the dimension (e.g. “man” vs. “woman” for gender) and then 3) use these to project each identity onto a line in the embedding space defined by those two dimension ends, giving a single number. Several approaches exist to complete steps 2) and 3) ( Joseph and Morgan 2020 ) . We follow prior work where possible for 2), and for 3), i.e. to calculate similarity, we use RIPA, the method described by Ethayarajh, Duvenaud, and Hirst ( 2019 ) . Finally, for each embedding model on each dimension, we then compute the Spearman correlation between the projections and the survey data.

Figure  3 shows that our three models all perform at least as well—but not better than—the baselines for projections onto age, all significantly improve over baselines in measuring perceived partisanship, and significantly improve over the baselines, except for Fine-tuned BERT, on perceived gender. Our models’ improvements over baselines are particularly salient in comparison to the RoBERTa and BERT baselines. Notably, we also see that our Bio-only model, based on word2vec performs well compared to the more complex models on this task. This suggests that for phrases that are prominent in bios, this model (which trains only on the bios themselves) may be preferred. However, the Bio-only model cannot extend beyond the vocabulary, and thus (as we will see) struggles with generalizability. Finally, Figure  3 also shows that the greatest jumps in performance for our models, relative to the baseline, are clearly on the partisan dimension.

Do Projections of Entire Bios Correlate with Human Judgements?

Our third evaluation assess the question, can our model capture perceptions of self-presentation in entire bios? To address this, we conduct a similar analysis as above, comparing the Spearman correlation of projections of our embedding models to mean ratings by Prolific respondents on a survey task. There are, however, four primary differences between the evaluation of single identities and the one presented here for full bios.

First, of course, is that we ask respondents for their perceptions of entire bios, rather than individual identities within bios. More specifically, we randomly sample 1,300 bios of users in our case study data, described below. Second, because in our case study we are interested in religiosity as well as age, gender, and partisanship, we add a question regarding perceived level of religiosity to the survey. Third, as opposed to selecting only one approach for defining ends of the semantic axis onto which embeddings are projected, we consider two approaches. The first follows our second evaluation and uses a combination of prior work and author intuition to define the terms at each end of the axis. Motivated to ensure accurate measurements for our case study, the second considers whether or not we can improve correlations with human judgement by constructing lists of terms for dimension endpoints that are informed by a qualitative analysis of bios. More specifically, we manually explore bios from the case study data described below that are not included in the survey study and use them to define the list of terms. We compare performance using both approaches here, but ensure that we compute results only on bios that do not include terms that explicitly define our endpoints . Fourth, we opt to only compare performance of SBERT and Fine-tuned SBERT, as other models fared poorly on one or both of the prior evaluations.

All other details of our evaluation generally match those in our second evaluation, save for the sample of Prolific users; see the appendix for details on this.

Figure  4 shows that the Fine-tuned SBERT model has a significantly higher correlation with human judgements on dimensions of partisanship and religion, regardless of how endpoints of the dimensions are defined. For gender and age, Fine-tuned SBERT performance shows no significant improvement over a non-fine-tuned SBERT model, but is also not significantly impacted by how dimension endpoints are defined. In contrast, for the SBERT model, in one case (age) our use of qualitative exploration to find in-domain sets of phrases to define dimensions significantly increases correlations with human judgement, and in the other (gender) it significantly decreases correlations. These results suggest that the Fine-tuned SBERT model is therefore more robust to the known challenge of defining “good” sets of phrases to define endpoints (Joseph and Morgan 2020 ) .

How do our Projections Compare to Other Measures at the User Level?

In our final evaluation, we focus specifically on projections of bios onto partisanship and explore 1) how well these projections correlate with a different measure of user partisanship (evaluating convergent validity), and 2) whether or not our measure of partisanship correlates in expected ways—and in a similar way to the other measure of user partisanship— with misinformation sharing (evaluating hypothesis validity Jacobs and Wallach 2021 ) . To conduct these evaluations, we make use of a pre-existing dataset of 374,684 Twitter users 1) for whom prior work (McCabe et al. 2022 ) has computed a standard measure of user ideology using user follower networks, and 2) for whom we have data on the sharing of low-quality news sites.

With respect to the partisanship measure we compare to, McCabe et al. ( 2022 ) apply a method pioneered by Barberá et al. ( 2015 ) that uses a combination of information about the partisanship of elite Twitter users and follower relationships to compute an estimate of user partisan ideology. McCabe et al. ( 2022 ) adopt the same approach, but update information about elites from the 2012 data used by Barberá et al. ( 2015 ) to 2020 data, and apply the approach to a large set of Twitter users that they linked to voter registration records using established methods (Hughes et al. 2021 ) . The work from McCabe et al. ( 2022 ) presents full details on implementation and an extensive validation of the measure in comparison to voter registration data; we therefore refer the reader to their work these details and focus here only on a comparison between their updated version of Barberá et al. ’s 2015 method and our partisanship measure using bio data.

With respect to the sharing of low-quality news, we focus on the proportion of URLs to low- and high-quality news websites shared on Twitter by these users from July 1st, 2020 through May 31st, 2021. We determine whether a URL comes from a low- or high-quality news website by making use of 1) the list produced by Grinberg et al. ( 2019 ) (who categorize sites into a binary high or low-quality distinction) and 2) the NewsGuard domain rating list. NewsGuard is an organization that maintains a widely-used (e.g Altay, Nielsen, and Fletcher 2022 ; Horne, Nørregaard, and Adalı 2019 ) list of news websites that are rated on a scale of 0-100 for information quality. We follow prior work and dichotomize their ratings into a binary low- or high-quality value for each site. We use a score of 60 as the threshold, following prior work (Lin et al. 2022 ) . Further, while we opt for a particular definition across these two lists, we note that prior work (Lin et al. 2022 ) has shown that various lists of misinformation domains are highly correlated, and thus that results for the study of misinformation are unlikely to be sensitive to these types of changes. Using these binary domain scores, we define our outcome variable for an individual user as the percentage of all URLs the user shares that come from a low-quality news site, divided by the total number of URLs shared from a domain listed in NewsGuard. We refer to this outcome as the proportion of low-quality shares .

Finally, for our bio-based measure, we use user bios collected in July of 2020 (i.e. within the same timeframe of the following data and misinformation sharing data), and project bios onto partisanship using the methods detailed in our evaluation of full bio embeddings (our third evaluation).

We find a correlation of 0.39 [0.387,0.393] between the bio-based projection measure of partisanship using our fine-tuned SBERT model and the partisanship estimates from McCabe et al. ( 2022 ) . This correlation is nearly double the correlation we find between the bio-based projection measure computed using the non-fine-tuned SBERT model and the estimates from McCabe et al. ( 2022 ) (0.197 [0.193,0.201]), and even higher than the correlation between the fine-tuned SBERT model and the non-fine-tuned model (0.347 [0.343,0.35]). This strong correlation, even when compared to reasonable baselines, gives us further confidence in the convergent validity of our measure—while we should not expect a measure based on a more private behavior (following) to correlate exactly with one based on a more public behavior (text in bios), we do see, as expected, a reasonably strong relationship.

We also find that these two measures show consistent estimates of the relationship between partisanship and misinformation sharing. These estimates, moreover, conform with what we would expect from prior work (Grinberg et al. 2019 ; Guess, Nagler, and Tucker 2019 ) . More specifically, Figure  5 shows the estimated proportion of low-quality shares from a binomial regression model where the independent variables are indicators for partisanship after bucketing each variable into 10 separate bins of equal numbers of users, respectively. 6 6 6 Binning is done to avoid assumptions about the precision of these proxy variables and to ease interpretation; bin sizes selected here are for visual clarity. Results are not, however, sensitive to this decision. All main effects in the model used to estimate the proportions shown in Figure  5 are significant at p ≤ .001 𝑝 .001 p\leq.001 italic_p ≤ .001 , and trends between the two different measures are consistent in showing that those furthest to the partisan right are most likely to share low quality news.

Misinformation Case Study

The previous evaluations show that our Fine-tuned SBERT model can project bios onto social dimensions of meaning in ways that correlate with how those bios are likely to be perceived by humans , and that the approach has both convergent validity and hypothesis validity in comparison to a different measure of user partisanship. Our case study uses the same dataset, but leverages our methodology to explore the link between self-presentation in bios and the rate of low- versus high-quality news sharing in the context of our two research questions. First, we explore the interaction between self-presentations of age and partisanship and their association with low-quality new sharing. Second, we consider the association between self-presenting as religious and misinformation sharing.

We note that while it would be possible for McCabe et al. ( 2022 ) to make use of additional voter registration data to, e.g., control for age, our tool is still useful for two reasons. First, most existing social media datasets are not connected to voter registration data, nor are the aligned with follower network data that could be used to apply the method from Barberá et al. ( 2015 ) . To this end, we are able to use our methods to replicate our analysis on a new dataset from the Twitter Decahose, which we could not do otherwise (see appendix for details). Second, we note that an analysis of religiosity is in any case not possible with existing voter registration data, as religiosity does not exist within versions of these data that have been provided to researchers in the past.

With respect to our first research question on the interaction between age and partisan self-presentation, we find that the direction of effects for age and partisanship generally match prior work, but that interaction effects not observed in prior work on demographics appear in our analyses. Figure  6 more specifically shows that users who self-present as older and right leaning is associated with a superlinear increase in proportion of low-quality news shared relative to being old or right-leaning.

Addressing our second research question, and using the same binning approach with univariate statistical models, we observe in Figure  6 B) that self-presenting as being highly religious is also associated with statistically significant ( p < .001 𝑝 .001 p<.001 italic_p < .001 ) jumps in the proportion of low-quality shares. As in the real world (Druckman et al. 2021 ) , our measures of religiosity and partisanship are highly correlated (at 0.76) , and thus we do not attempt to tease out whether this effect is particularly salient conditioned on partisanship. More specifically, we avoid interpretation of coefficients in a model with both of these variables because interpretation of regression coefficients with strongly co-linear variables is prone to misidentification of effect size and statistical significance (Gregorich et al. 2021 ) .

We do find, however, that religiosity adds additional predictive power, in that adding religiosity as a predictor to a model with partisanship results in a statistically significant increase ( p < .001 𝑝 .001 p<.001 italic_p < .001 ) in predictive power. Descriptive statistics do, however, provide some evidence into a potential interactive relationship between partisanship, religiosity, and sharing content from low-quality sites. Specifically, Figure  9 in the appendix shows that partisanship and religiosity may have a multiplicative association with sharing content from low-quality news sites. Participants who present as both right-leaning and religious have, on average, higher odds of sharing low-quality news links than users who present as only right-leaning or only religious. Future experimental work targeting this specific interaction effect in ways that avoid endogeneity concerns might therefore be of interest.

Critically, all findings presented here extend beyond this particular dataset to a second large dataset of misinformation sharing drawn from a broader population in the Twitter Decahose. These replication results are presented in the appendix.

Discussion and Conclusion

We present, evaluate, make public, and make use of new methods to project Twitter bios onto meaningful social dimensions. Methodologically, our contribution is not innovation in algorithm development, but in the application of standard algorithms to carefully constructed training datasets and training set-ups to build entity-centric identity embedding spaces (where identities that are commonly presented for the same people are represented in a similar space). Notably, our estimates of self-presentation do not use other user behaviors (e.g. retweets).

After extensively validating our proposed methods, we present a case study on two open questions in the literature on misinformation sharing online. In response to our first question, we find an interaction effect between age and partisanship- that Twitter users presentinand Republican share a much higher proportion of low-quality news. With respect to our second research question, we similarly find that individuals who self-present as religious, perhaps especially on the political right, are much more likely to share a higher proportion of low-quality news. Our results have two important implications. With respect to combating misinformation online, while much work has considered interventions targeted along partisan (Martel et al. 2024 ) or age-based (Brashier and Schacter 2020 ) , our results provide evidence that we should be considering even more narrow interventions targeted at older and right-leaning Americans. With respect to better understanding the misinformation environment online in the U.S., our work provides critical empirical validation of theories that suggest religiosity is an important component of the quality of information consumed and spread online (Druckman et al. 2021 ) .

However, our work contains a number of limitations that should be considered. Specific to our case study, we follow previous work that uses a domain-based approach to identify misinformation sharing (Grinberg et al. 2019 ; Guess, Nagler, and Tucker 2019 ; Moore, Dahlke, and Hancock 2023 ) , which includes posts that share a URL with a negative annotation. However, like previous work, we find the number of such posts to be a small proportion of all shares. While other work referenced above suggests our efforts should extend to other social media sites, Twitter, like all sites, has particular elements that limit our ability to generalize claims about self-presentation elsewhere, in particular to “offline” behavior settings (DeVito, Walker, and Birnholtz 2018 ) . In particular, our models learn cultural associations from the majority white, male, younger, and left-leaning users of Twitter (Hughes et al. 2021 ) . Similarly, our survey evaluation data is largely drawn from white, American women, which limits their generalizability.

Our work is also contextualized in a particular period of time, and thus may not be responsive to significant shifts in social identity. All of these, and results described in the paper, emphasize the contextualized nature of our trained models and datasets. While we hope that future work might expand beyond them, others should consider using our publicly available code to fine-tune our models on their own data. Finally, our case study is necessarily terse, and does not explore a number of additional important and interesting questions. In particular, there may be other interesting dimensions of self-presentation that may be interesting to social scientists interested in misinformation sharing on social media. Our work also has ethical implications, which we discuss in more detail in the Ethics Statement below, as well as in the required paper checklist. Our hope, however, is that the proposed, and public, methods allow future efforts that explore new questions that link identity and behavior on Twitter and other sites with social media bios.

Acknowledgements

NM and KJ were supported by an ONR MURI N00014-20-S-F003 and by NSF IIS2145051. SM was supported by the John S. and James L. Knight Foundation through a grant to the Institute for Data, Democracy, & Politics at the George Washington University. RB was supported by the MSCA Grant Agreement No. 101073351 at GESIS Leibniz Institute for the Social Sciences.

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Paper Checklist

One can crudely separate the way that members of the NLP community acknowledge sociocultural associations embedded in language into three camps. In the first, acknowledgement is largely non-existent, with scholars either choosing to ignore the social implications of language or arguing that it is not within their purview to address them. In the second, scholars concerned with the potential that NLP tools might reify biases in language have sought to develop tools to reduce or remove the use of biased tools in production. Example efforts include the literature on “debiasing” embedding spaces—where scholars aim to remove meaning on “unwanted dimensions” (i.e. on social dimensions of meaning) and keep it only on “objective” dimensions (i.e. on more traditional semantic dimensions)— and work to carefully elaborate how problems can arise from NLP tools that do not critically engage with the social implications of language (Blodgett et al. 2020 ; Field et al. 2021 ) .

While we strongly support the latter line of critical scholarship, we fall into a third camp of NLP researchers, who see the potential for NLP methods that capture social meaning in language to help inform our understanding of society and its behaviors (Kozlowski, Taddy, and Evans 2019 ; Bailey, Williams, and Cimpian 2022 ; Garg et al. 2018 ) . As individuals who are supportive of existent critical literature, and who are still building methods that are inherently engaging in stereotyping, we must accept that our methods can be used not only to measure perceptions and self-presentations but also to apply them for nefarious purposes, such as racially-biased targeted advertising (Ali et al. 2019 ) . The ultimate ethical question that we must address, then, is whether we believe that our measurement strategies will ultimately do more harm than good.

Our decision to submit the present work for consideration reflects our belief, after deliberation, that the potential benefits of our work outweigh the potential dangers. From a benefits perspective, we show that our work can help us understand the (mis)information environment on Twitter, and hope in the future to use these methods to better understand 1) how hegemonic voices are often given outsized attention on social media platforms, and 2) how attacks on marginalized communities changed along with the political climate in the United States. From a misuse perspective, we do not believe that the methods we have developed here are more effective at targeting individuals based on stereotyped demographics than the tools already in existence elsewhere, tools which use orders of magnitude more compute data and power. As such, while there are real dangers with being misclassified in a particular way online, we 1) emphasize throughout the paper that we focus only on how someone is likely to be perceived based on what is in their bio, and do not claim to be able to classify some “true self” of users, and 2) expect that if one wanted to engage in such a prediction activity, it could be done better with methods that focus specifically on this task.

A similar value judgement was applied to the other ethical question in our work: whether or not to publicly release parts of our data. Ultimately, restrictions on the Decahose have made it challenging to share data. However, given recent literature in the ICWSM community (Assenmacher et al. 2020 ) , we believe the appropriate course of action is to release training data on a per-case basis, as potential dataset users contact the last author of this paper. However, we believe that the release of our (fully deidentified) survey data and basic case study data does not serve any inherent risks for users in our dataset, and thus have opted to do so in the Github repository for this work. We believe that the utility of these data to the scientific community, both for replicability and extension, outweigh the dangers of data release. Of course, in all cases, data and methods usage is a continually evolving process, and we will re-evaluate this value judgement as often as is needed.

For most authors…

Would answering this research question advance science without violating social contracts, such as violating privacy norms, perpetuating unfair profiling, exacerbating the socio-economic divide, or implying disrespect to societies or cultures? As noted above, there are privacy concerns in our work that we have carefully considered and weighed relative to the benefits of our work.

Do your main claims in the abstract and introduction accurately reflect the paper’s contributions and scope? Yes

Do you clarify how the proposed methodological approach is appropriate for the claims made? Yes

Do you clarify what are possible artifacts in the data used, given population-specific distributions? Yes

Did you describe the limitations of your work? Yes

Did you discuss any potential negative societal impacts of your work? Yes, see the Ethics Statement

Did you discuss any potential misuse of your work? Yes, see the Ethics Statement

Did you describe steps taken to prevent or mitigate potential negative outcomes of the research, such as data and model documentation, data anonymization, responsible release, access control, and the reproducibility of findings? Yes, see the Ethics Statement

Have you read the ethics review guidelines and ensured that your paper conforms to them? Yes

Additionally, if your study involves hypotheses testing…

Did you clearly state the assumptions underlying all theoretical results? NA

Have you provided justifications for all theoretical results? NA

Did you discuss competing hypotheses or theories that might challenge or complement your theoretical results? NA

Have you considered alternative mechanisms or explanations that might account for the same outcomes observed in your study? NA

Did you address potential biases or limitations in your theoretical framework? NA

Have you related your theoretical results to the existing literature in social science? NA

Did you discuss the implications of your theoretical results for policy, practice, or further research in the social science domain? NA

Additionally, if you are including theoretical proofs…

Did you state the full set of assumptions of all theoretical results? NA

Did you include complete proofs of all theoretical results? NA

Additionally, if you ran machine learning experiments…

Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? See the Github link in the first footnote

Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? See the main text as well as the appendix below

Did you report error bars (e.g., with respect to the random seed after running experiments multiple times)? Yes

Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)? Yes

Do you justify how the proposed evaluation is sufficient and appropriate to the claims made? Yes. Specifically, we use a number of clear, competitive, and comparable baselines

Do you discuss what is “the cost“ of misclassification and fault (in)tolerance? Yes, see the Ethics statement.

Additionally, if you are using existing assets (e.g., code, data, models) or curating/releasing new assets, without compromising anonymity …

If your work uses existing assets, did you cite the creators? Yes.

Did you mention the license of the assets? To the best of our ability, we believe that nothing we have provided requires this, but we will update as necessary.

Did you include any new assets in the supplemental material or as a URL? Yes.

Did you discuss whether and how consent was obtained from people whose data you’re using/curating? We provide details on the dataset, acknowledging that consent was approved in surveys as IRB requires. Social media users are non-consenting, which we acknowledge in our Ethics statement.

Did you discuss whether the data you are using/curating contains personally identifiable information or offensive content? Yes, see the ethics statement

If you are curating or releasing new datasets, did you discuss how you intend to make your datasets FAIR? In progress for the camera ready version

If you are curating or releasing new datasets, did you create a Datasheet for the Dataset? In progress for the camera ready version.

Additionally, if you used crowdsourcing or conducted research with human subjects, without compromising anonymity …

Did you include the full text of instructions given to participants and screenshots? We use a protocol from a prior work, which we do reference.

Did you describe any potential participant risks, with mentions of Institutional Review Board (IRB) approvals? Yes, our studies are IRB approved.

Did you include the estimated hourly wage paid to participants and the total amount spent on participant compensation? Yes.

Did you discuss how data is stored, shared, and deidentified? Yes.

Appendix A Appendix

Bios from the twitter decahose.

The center column of Table 1 provides summary statistics for the Twitter bio data we construct. We begin with a sample of 15,459,872 distinct Twitter bios from users who posted a tweet in 2020 that was found in the Decahose, and who are specified as English-language users by the Twitter API. In order to maintain a focus on culturally-salient identities, we limit the size of the vocabulary to identities used in at least 100 unique Twitter bios in the training set. Further, because we are interested in associations between identities, we further remove Twitter bios that contain less than 2 identities. After these cleaning steps, our training and test data consists of 3,534,903 and 1,546,001 distinct bios respectively with 22,516 unique identities in the vocabulary. We then follow the approach outlined in the main text to produce the main test dataset and the generalizability test set. Note that the size of each of these splits can be larger than the size of cleaned test dataset, because we can generate multiple instances from a given bio by randomly selecting different targets; i.e. we can generate multiple test instances out of each of profile description by selecting multiple pairs of X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT and X t i subscript superscript 𝑋 𝑖 𝑡 X^{i}_{t} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT .

Finally, to provide further insight into the data, Table 2 showcases the top 7 identities in terms of overall frequency in the training data and 7 of the least frequent identities to show that the tail still contains meaningful phrases.

Single Identity Survey Data

A complete, aggregated copy of this data is provided in the Github for this paper. Our survey study was ruled exempt by the IRB at [REMOVED]. Each respondent rated between four and seven identities, and each identity was given to at least 3 respondents. Respondents were paid an average of $12/hour. Respondents are from a convenience sample, as recent work has suggested that the cost efficiency of convenience samples does not necessarily impact data quality (Coppock, Leeper, and Mullinix 2018 ) . The median age of our sample is 32. Of the 140 respondents, 88 reported their sex as female, 49 as male, and 4 noted other/did not provide. Our sample, like Twitter, was overwhelmingly White; 105 (75%) of the sample reported as White.

We here provide two minor additional details on our survey data. First, it is of note that in contrast to prior work, we focus explicitly on priming respondents to think of social media users, asking, for example, “If you saw [identity] in a social media biography, would you expect that individual to be” and then provided a Likert scale ranging from (e.g.) “Always [a] Democrat” to “Always [a] Republican.” Second, we emphasize that other procedures, including tutorial materials, task details, and attention checks, follow the publicly available materials from Joseph and Morgan ( 2020 ) .

Entire Bio Survey Data

A complete, aggregated copy of this data is provided in the Github for this paper.

We use responses from approximately 730 Prolific respondents. Because of a temporary issue with the survey, some respondents were approved for pay without taking the study, we report demographics here on all respondents here because of this issue. The median age of respondents was 37. Reported sex was more balanced than the sample for the single identity study, 51% and 44% of respondents reported a sex of female or male, respectively. As above, however, a majority of the sample (65%) reported as White. Respondents were paid an average of $12/hour. Full details are provided in the Appendix for the interested reader.

Two final notes are in order. First, with respect to the difference between the two surveys is that because we focus on individual user bios, we in this study ask respondents to assess the likelihood that the individual user who has this bio is, e.g., a Democrat or Republican, rather than asking (as above) about the probability that an individual who holds a given identity is, e.g., a Democrat or Republican. Second, we note that we drop the 5% of respondents whose responses were furthest from all other respondents, on average, across all identities and dimensions (after standardizing measures across dimensions). This results in a final sample of 1,273 bios analyzed here and provided in the Github repository.

Replication with Data from the Decahose

We replicate findings using the case study dataset analyzed in the main text with a different dataset, broader in scope, drawn from the Decahose. A complete, anonymized copy of this replication data is provided in the Github for this paper. For each user, it contains the number of URLs they shared that link to low- and high-quality domains, as identified by NewsGuard, and projections of their bios onto the four dimensions of interest to the case study.

We begin with a sample of roughly 290,000 users who tweeted at least one NewsGuard URL in the decahose in 2020. Of this sample, 143,883 users were 1) still active when we recollected tweets in 2022, and 2) had a non-empty English-language bio. It is possible that our use of langdetect could bias our sampling of what is considered English language (Blodgett, Green, and O’Connor 2016 ) ; as such, we manually evaluate it. To do so, we had three research assistants label 900 bios as English, not English, or Vague. The annotators had a Krippendorf’s alpha agreement score of 0.81 and agreed on 90% of the bios with the library. More specific to our case study, 93% of the bios that langdetect measured as English were also annotated as English by all the annotator. The main reason for mis-classification of the bio’s language was that some bios consisted of phrases from multiple languages. We therefore believe that this step did not bias our results in any obvious way.

Of these remaining 143,883 users who matched our initial sampling criteria, a remaining 108,554, or 75.4%, had at least 5 shares of URLs in NewsGuard, which we considered a minimum for estimating proportions. The median user had 49 shares of high quality news website URLs and 3 shares of low quality news website URLs. In total, these users shared 11,735,521 links to NewsGuard domains we assess in our study.

Figure  7 replicates findings from Figure  6 A) in the main text, namely, observe a similar increase in the association between self-presented (older) age and misinformation sharing as we see an increase in right-leaning self-presentation. Figure  8 replicates Figure  6 B).

Descriptive Statistics Partisanship and Religiosity

Figure  9 shows a descriptive statistic that provides some evidence that religiosity and partisanship have an interactive effect on misinformation sharing. However, as noted in the main text, correlations between these variables make it challenging to assess the statistical significance of these variables relative to each other; in particular, there are few left-leaning accounts that also present as religious.

Distributional Semantic Models (Baselines)

For all DSM baseline models except Sentence Bert, including BERT-base, RoBERTa-base and BerTweet-base we experimented using open-source implementations on Hugging Face transformers library 7 7 7 https://huggingface.co/docs/transformers/ . For the Sentence-Bert baseline, we used the mpnet-base pre-trained model and the implementation given by open-source Sentence Transformers library. 8 8 8 https://github.com/UKPLab/sentence-transformers

Bio-only Model

To select hyperparameters, we use 10% of the training data as a validation dataset. The primary hyperparameter we tuned was whether to use a Skip-Gram or C-BOW model. We ultimately chose a Skip-Gram model for Twitter and a C-BOW model for Wikipedia, with the other hyperparameters as specified in the main text. Model training took under an hour on a personal laptop. We used the open-source implementation of word2vec in gensim 9 9 9 https://radimrehurek.com/gensim/ for our experiments.

We here briefly provide additional intuition for our Fine-tuned SBERT model. Given a dataset of pairs of identity phrases with a label denoting the anchor-positive pair or anchor-negative pairs, we input the pair into the pipeline shown in Figure 10 and extract the latent embeddings of each of the identities. Then we calculate the cosine similarity of the embeddings and backpropagate the mean squared error loss with the label through the network. In this work we fine-tuned a mpnet-base Sentence Bert model since it had the same model size as a BERT-base and the pre-trained model was available online.

Further details on Baseline Models

For all DSM baseline models except Sentence Bert, including BERT-base, RoBERTa-base and BerTweet-base we experimented using open-source implementations on Hugging Face transformers library 10 10 10 https://huggingface.co/docs/transformers/ . For the Sentence-Bert baseline, we used the mpnet-base pre-trained model and the implementation given by open-source Sentence Transformers library. 11 11 11 https://github.com/UKPLab/sentence-transformers .

Other Baseline Models Considered

In addition to the three baseline models discussed in the text, we also experimented with a pair of other sensible options.

First, we expected that a DSM pretrained on Twitter would be a strong baseline to compare to, and thus experimented with additional models pre-trained specifically on Twitter data (Nguyen, Vu, and Tuan Nguyen 2020 ) . We use the fine-tuned BERT model on Twitter data proposed by (Nguyen, Vu, and Tuan Nguyen 2020 ) . They propose a BERT-base model fine-tuned using a corpus of 850M English Tweets. However, we find that model performance was no better than the other, more widely used baseline DSMs we proposed in the main experiments.

Second, it seemed reasonable that by first restricting a baseline DSM to known dimensions of social meaning, we could improve their performance. Consequently, we considered baselines where we first projected down all baseline models into the core dimensions of meaning noted by Joseph and Morgan ( 2020 ) before the evaluation tasks. In both cases, however, our intuitions did not match empirical reality. These models failed to outperform the baselines used in the main text, and thus we restrict our analysis to the baselines discussed in the main text.

Generating Embeddings for the Predictive Experiment

In order to build inputs to the network, since X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT is a list of personal identifiers, to calculate the latent embedding L r i subscript superscript 𝐿 𝑖 𝑟 L^{i}_{r} italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT for it, depending on the model, we follow different procedures. For the Bio-only model, we simply measure the average latent vector of all phrases in X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT according to ( 1 ). For the Fine-tuned models, as well as the baseline contextualized language models discussed below, we stitch the words in X r i subscript superscript 𝑋 𝑖 𝑟 X^{i}_{r} italic_X start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT together with comma and create a sentence S r i subscript superscript 𝑆 𝑖 𝑟 S^{i}_{r} italic_S start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT . We then measure L r i subscript superscript 𝐿 𝑖 𝑟 L^{i}_{r} italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_r end_POSTSUBSCRIPT according to Equation ( 2 ). Equivalently, this means that for the BERT based models we take the embedding of [CLS] token for pooling and for the Sentence Bert based models we follow the original work and take the average of all token embeddings.

Projection to Social Dimensions

In order to project a piece of text (either a full bio or a single identity) onto a specific dimension, we have to first define the end-points of that dimension. Table 3 and 4 outline the original and in-domain dimension end-points that we talk about in this paper, in particular in our Entire bio projection evaluation. To generate embeddings for an end-point, we assume each end-point is an instance in X 𝑋 X italic_X and follow the approach outlined above to generate embeddings for each end-point of the dimension d 𝑑 d italic_d and call them E d 1 superscript subscript 𝐸 𝑑 1 E_{d}^{1} italic_E start_POSTSUBSCRIPT italic_d end_POSTSUBSCRIPT start_POSTSUPERSCRIPT 1 end_POSTSUPERSCRIPT and E d 2 superscript subscript 𝐸 𝑑 2 E_{d}^{2} italic_E start_POSTSUBSCRIPT italic_d end_POSTSUBSCRIPT start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT respectively. Having the embedding of both poles of the dimension, we calculate the difference vector according to Equation 3 , and calculate the embedding of the target text using the same approach to a vector L i superscript 𝐿 𝑖 L^{i} italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT . Then we follow the projection approach outlined in (Ethayarajh, Duvenaud, and Hirst 2019 ) to normalize all vectors and then calculate the projection value of L i superscript 𝐿 𝑖 L^{i} italic_L start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT onto dimension d 𝑑 d italic_d according to equation 4 .

Error Analysis of The Predictive Task

Our understanding of the proposed models is improved by studying where errors occur. Here, we briefly present both quantitative and qualitative reflections on the major sources of error for the Bio-Only and Fine-tuned SBERT models. At a high level, we find that pre-training helps the Fine-tuned SBERT model on predictions requiring knowledge of phrase composition (e.g. that “mother” and “mother of two” convey similar meanings), but appear to cause it to struggle on infrequent identities, which the Bio-only model is better able to capture meanings of from the bio data alone.

Quantitatively, Figure  11 shows that both models performed best, and roughly equally well, on the most frequent identities, but that differences appeared in how the models fared elsewhere. The Bio-only model’s ranking distribution (the marginal density plot on the right-hand side of Figure  11 ) was bimodal, with a large number of high (poor performance) and low (strong performance) ranks for test points. Perhaps unsurprisingly, we find qualitatively that the poor performance of the Bio-only model relative to the Fine-tuned SBERT model largely came from an inability 1) to learn from compositional identities or 2) to leverage relevant external knowledge. These issues seemed to impact the model most for moderately frequent target identities, those appearing between 300-10,000 times in the training data. With respect to 1), for example, when provided the Twitter bio “mother of two, restaurant owner, partly retired, hockey coach” 12 12 12 This bio has been modified to protect user privacy , the Bio-only model ranks the correct held-out identity, “wife,” among the least likely. In contrast, the Fine-tuned SBERT model correctly ranks “wife” in the Top 1%. The core difference is that the Fine-tuned SBERT model, but not the Bio-only model, leverages the gender stereotype implied by the “mother” portion of the phrase “mother of two.” With respect to 2), there were several cases where external knowledge from the pre-trained model benefited the Fine-tuned models. For example, the Fine-tuned models, but not the Bio-only models, were able to recognize the similarity between the identities “follower of ISKSON” (a Hindu religious organization) and “proud Hindu.” Both of these were relatively infrequently used.

In contrast, relative to the Bio-only model, Fine-tuned models struggled with the most infrequent identities, in particular the roughly 18% of identifiers in the test set that occurred fewer than 300 times in the training data. In these cases, as in prior work entity-centric domain adaptive work (Field and Tsvetkov 2019 ) , the Fine-tuned models seemed to rely too heavily on knowledge from the pre-trained model and not enough to domain-relevant context. In contrast, the identity-centric model seemed to benefit on the prediction task from overfitting to stereotypical knowledge for these rarer phrases. The Fine-tuned models also struggled when presented with identities, such as Twitter-specific acronyms, that were likely rare in the DSM data, but more frequent on Twitter. Here, pre-training seemed to induce noise, leading the Fine-tuned models to predict somewhat randomly.