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How to run and measure social media experiments

Written by by Jamia Kenan

Published on  February 22, 2023

Reading time  7 minutes

You already know that social moves fast. What worked for your brand a few months ago may not be relevant today. This is why social media managers thrive when they embrace a mindset of continual learning and development. Improving your social media marketing strategy requires frequent reevaluation and iteration, and running social media experiments is an essential part of the process.

Whenever you have a hypothesis, question or challenge related to your social media marketing strategy, social media experiments can provide actionable next steps. Their results provide concrete evidence to support your case for more resources or reasoning behind switching up your current content.

Social media experiments not only challenge your current strategy, but can also open opportunities to try something different—such as a new social media network or feature—and determine if it’s effective for your target audience. Experimentation can also reveal faster ways to reach your goals, help you avoid costly mistakes and uncover new information about your audience.

Grab your metaphorical safety goggles, lab coat and test tubes because in this article we’re going to walk through the steps for running and measuring successful social media experiments.

7 Steps for running a social media experiment

With these seven steps, you’ll be testing on social media with ease in no time:

• Formulate a hypothesis
• Choose the right type of social media experiment
• Select your metrics and the network you want to test
• Define the duration of the social media experiment
• Select your variables and control
• Conduct the social media experiment
• Analyze and share the results of your experiment

 1. Formulate a hypothesis

Before you begin, you’ll need a basic understanding of the following:

• The overall goals of your business
• Your current social strategy, including overarching goals per platform
• Your audiences by social network
• Your current social performance
• The questions, notions and ideas you wish to test

Prioritize a hypothesis that will result in the biggest impact on your team’s top-level social media goals . Avoid running several tests at once because it can lead to inconclusive results, especially if you’re focused on managing organic social.

If you’re using Sprout, you can learn about your audiences and performance by channel through our cross-network reports (like the Post Performance Report) or competitor reports (like the Instagram Competitors Report).

To dive even deeper into understanding your audience, use Sprout’s Advanced Listening tools. With Listening, you can build queries to track and analyze social conversations, pin down trends and view consumer sentiments. Seeing the data behind what your audience is talking about and the content they engage with will help you formulate a hypothesis.

2. Choose the right type of social media experiment

Now that you have a hypothesis, it’s time to select the type of social media experiment you will conduct to prove your theory.

There are two main types you can choose from: A/B testing and multivariable testing.

Social media experiment ideas for A/B tests

One of the most common types of social media experiments, an A/B test is an experiment where you change only one variable and keep everything else the same. These types of tests are an excellent way to pinpoint improvements that will make a measurable impact. Some common A/B tests on social include:

• Content types: video vs. a link, photo, GIF, etc.
• Captions: long vs. short
• Copy: question vs. statement, emojis or hashtags
• Images: illustrations vs. photography or animation
• Posting time: Monday at 9:00 a.m. vs. Friday at 4:00 p.m.

For example, if you wanted to test which content type is the most engaging on Instagram Stories, your team could test photo content against video content. The content type would change, but you would use the same caption and post at the same time and day of the week, one week apart.

Using Sprout, the Atlanta Hawks ‘ social team tested a casual approach to videos at community events. A player shot a hand-held video that was compared to the performance of more produced social videos. The casual video format proved to be more successful and sharing the performance data was a major win for the social team.

Social media experiment ideas for multivariable testing

As its name implies, multivariable testing alters two or three variables at once. However, since you’re experimenting with more elements, analyzing and interpreting data can be harder. You’ll also need a large audience to avoid skewing the test.

Some multivariable tests include:

• Short-form animated video vs. long-form live action video
• Varying tones of voice paired with or without emojis
• Multiple call-to-action buttons with different featured images
• Different content types with various captions
• Same content type but different days/times and platforms to see which resonates the most, like Instagram vs. TikTok

Sprout’s social team conducted several multivariable tests to help develop our TikTok marketing strategy , as you’re about to read in the next step.

3.  Select your metrics and the network you want to test

Establish the key metric you want to measure successful content against. This can include impressions, traffic to a particular page such as your brand’s website or a gated resource, and engagement metrics (Think: likes, clicks, comments or shares).

The channel you choose to conduct your experiment will depend on what you’re testing and the social media network you use the most to post that kind of content. Use your network-specific data to inform this decision. Read some of Sprout’s Insights resources to learn which content types perform the best on which platforms.

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When our social team started testing TikTok, the main goal was to increase awareness among our target audiences. Accordingly, we selected impressions, video views, profile views and audience growth as key performance indicators.

4. Define the duration of the social media experiment

Don’t fall into the common mistake of not defining a time frame for your social media experiment. Remember that social media strategy is a long game–give time for new initiatives to grow and develop.

Your reporting window depends on your budget, audience size and KPIs, but the most important factor is to reach statistical significance.

Statistical significance refers to the likelihood your test results are the outcome of a defined cause and not chance. To reach statistical significance, you’ll need a large sample size and a control. For example, a sample size of 1,000 is stronger than 100, and your control would be the piece of content you do not change.

Set a duration and look for statistical significance. What are the significance changes? After your testing period, consider optimizing content that didn’t work during that timeframe instead of hitting the breaks on posts that aren’t resonating immediately.

While experimenting with TikTok, the social team reported results after four months since there was enough data available to analyze. They also set a weekly update to our internal social dashboard to continue testing and learning, along with iterating strategy, if needed.

During the first four months, we discovered views for every TikTok remained consistent, with an average of 535 views per video. We were also able to confirm our thoughts/assumptions about the For You Page (FYP) and the TikTok algorithm—each consistently pushed out content to our target audience (social media specialists, managers, digital marketers, etc.).

5. Select your variables and control

If you’re using A/B testing, consider all of the elements of your content that could influence your test results to ensure you’re only testing one variable. Also select your control, which is the content that will not change. For example, if you’re testing images, make sure to not change the copy, audience, timing, etc.

In our social team’s multivariable TikTok experiments, they tested several variables including formats, themes and creative considerations like music, sounds and closed captions.

In the example below, 91% of views came from the FYP, 5% came from a personal profile view and 1% came from direct followers–confirming their hypothesis that the FYP and the algorithm were the key drivers pushing out content to our target audience.

@sproutsocial It’s no secret that social teams are on the path to extreme burnout. @J A Y D E shares why it’s time for leaders to take action. #foryou #socialmediamarketing #socialmediamanager #socialmediatips #socialmedia #foryoupage ♬ Cloudy Sky – Tundra Beats

If you use Sprout, you can use tagging to track the performance of your control and the test post.

6. Conduct the social media experiment

Now it’s time to execute! Use Sprout’s Publishing tools to seamlessly plan, create, optimize and post your content for the experiment. For example, you can use Sprout’s ViralPost® technology to post at optimal send times.

Use the Tag Performance Report to organize, run and analyze your social media experiment results, including your paid campaigns.

Read our guide on creative testing for more tips and examples for conducting social media experiments.

7. Analyze and share the results of your experiment

Review the results of your experiment to identify new opportunities or add insights to your records.

If you’re trying to gain executive buy-in, especially for further testing or resources, you’ll need to communicate and create an effective data story to highlight why your company will benefit from your suggested next steps.

Using Sprout, you can easily access automated, presentation-ready reports to help illustrate your data story. Create custom reports, like this Facebook Performance Summary that includes impressions, engagements, post link clicks and publishing behavior for various content types:

Use experiments to optimize engagement and growth

Here’s a quick overview of the seven steps:

Good luck on your journey to embracing curiosity and thinking like a scientist—your social strategy will thank you.

This article is an excellent first step, but there’s so much more to learn about social media experiments. Step into the (virtual) lab yourself and get a hands-on experience, by signing up for a free trial .

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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Prevent plagiarism. Run a free check.

Step 1. ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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What Makes a Good Hypothesis? Essential Criteria and Examples

A well-formulated hypothesis is a cornerstone of scientific research, providing direction and focus for investigations. It serves as a bridge between theory and experiment, guiding researchers in their quest to explore, test, and validate scientific phenomena. In this article, we will delve into what makes a good hypothesis by examining its essential criteria and providing illustrative examples.

Key Takeaways

• A good hypothesis should be clear and precise, avoiding vague language and ambiguity.
• It must be testable and falsifiable, meaning it can be supported or refuted through experimentation.
• Grounding in existing knowledge is crucial; a hypothesis should be based on prior research or established theories.
• Formulating a hypothesis involves identifying variables and constructing if-then statements to define cause-and-effect relationships.
• Common pitfalls in hypothesis development include vagueness, double-barreled hypotheses, and lack of relevance to research objectives.

Defining a Hypothesis in Research

A hypothesis is a foundational element in scientific research, serving as a proposed explanation for a phenomenon that can be tested through experimentation and observation. It is a precise, testable statement predicting the outcome of a study, typically involving a relationship between an independent variable (what the researcher changes) and a dependent variable (what the researcher measures).

Essential Characteristics of a Good Hypothesis

A well-crafted hypothesis is fundamental to any research endeavor. It serves as a guiding framework for your study, ensuring that your research is focused and meaningful. Here are the essential characteristics that define a good hypothesis:

Formulating a Testable Hypothesis

Creating a testable hypothesis is a crucial step in the research process. A well-formulated hypothesis should be specific and measurable , allowing for clear and definitive testing. This section will guide you through the essential steps to ensure your hypothesis is both testable and meaningful.

Common Pitfalls to Avoid in Hypothesis Development

Avoiding vagueness.

One of the most frequent mistakes in hypothesis development is formulating vague or ambiguous hypotheses . A well-defined hypothesis should be clear and specific , leaving no room for multiple interpretations. For instance, instead of saying, "There is a relationship between study habits and academic performance," specify the type of study habits and the metrics for academic performance.

Steering Clear of Double-Barreled Hypotheses

A double-barreled hypothesis combines two or more variables in a single statement, making it difficult to test each variable independently. For example, "Increased exercise and a balanced diet improve mental health" is problematic because it conflates two distinct variables. Instead, separate the hypotheses: "Increased exercise improves mental health" and "A balanced diet improves mental health."

Ensuring Relevance to Research Objectives

Your hypothesis must align with your research objectives. Irrelevant hypotheses can lead to wasted resources and time. Ensure that your hypothesis directly addresses the core question of your research. For example, if your research focuses on the impact of social media on teenage self-esteem , a hypothesis about social media's effect on adult self-esteem would be misaligned.

By avoiding these common pitfalls, you can develop a robust and testable hypothesis that will significantly enhance the validity of your research.

Examples of Effective Hypotheses

Hypotheses in social sciences.

In social sciences, hypotheses often explore relationships between variables such as behavior, attitudes, and social structures. For instance, a hypothesis might state, "Individuals who participate in community service are more likely to report higher levels of life satisfaction." This hypothesis is clear and specific , making it testable through surveys or observational studies.

Hypotheses in Natural Sciences

Natural sciences frequently involve hypotheses that predict natural phenomena or biological processes. An example could be, "Plants exposed to classical music will grow taller than those that are not." This hypothesis is grounded in existing knowledge about the effects of sound on plant growth and can be tested through controlled experiments.

Hypotheses in Applied Research

Applied research often aims to solve practical problems, leading to hypotheses like, "Implementing a four-day workweek will increase employee productivity." This hypothesis is relevant to organizational studies and can be tested by comparing productivity metrics before and after the implementation of the new work schedule.

Evaluating and Refining Hypotheses

Peer review and feedback.

Engaging in peer review is crucial for refining your hypothesis. Soliciting feedback from colleagues or mentors can provide new perspectives and identify potential weaknesses. This collaborative approach ensures that your hypothesis is robust and well-grounded in targeted research .

Iterative Refinement

Hypothesis development is an iterative process. After initial feedback, you should revisit and revise your hypothesis. This may involve adjusting variables, rephrasing for clarity, or incorporating new data. The goal is to enhance the testability and precision of your hypothesis.

Aligning with Research Design

Your hypothesis must align with your overall research design. Ensure that it is compatible with your methodology, data collection techniques, and analysis plan. This alignment is essential for the hypothesis to be effectively tested and validated within the context of your study.

Evaluating and refining hypotheses is a crucial step in any research process. It allows you to test your assumptions and improve the accuracy of your findings. If you're struggling with this phase, our step-by-step Thesis Action Plan can guide you through it with ease. Visit our website to learn more and claim your special offer now!

In conclusion, crafting a good hypothesis is a fundamental step in the scientific method and essential for conducting meaningful research. A well-formulated hypothesis should be clear, concise, and testable, providing a predictive statement that can be empirically evaluated. By ensuring that your hypothesis is grounded in existing literature and theory, you enhance its validity and relevance. The examples and criteria discussed in this article serve as a guide to help researchers develop robust hypotheses that can withstand rigorous testing and contribute valuable insights to their respective fields. Ultimately, a strong hypothesis not only guides the direction of your research but also lays the foundation for scientific discovery and advancement.

Frequently Asked Questions

What is a hypothesis in research.

A hypothesis is a testable prediction about the relationship between two or more variables. It serves as a foundation for scientific inquiry, guiding the research process and helping to formulate experiments.

What are the essential characteristics of a good hypothesis?

A good hypothesis should be clear and precise, testable and falsifiable, and grounded in existing knowledge. It should also include an if-then statement that defines the relationship between variables.

How do you formulate a testable hypothesis?

To formulate a testable hypothesis, identify the variables involved, construct an if-then statement, and ensure that the hypothesis is measurable. This process helps in designing experiments that can validate or refute the hypothesis.

What are common pitfalls to avoid when developing a hypothesis?

Common pitfalls include vagueness, double-barreled hypotheses (addressing more than one issue at a time), and lack of relevance to the research objectives. Avoiding these pitfalls ensures that the hypothesis is clear and focused.

Can you provide examples of effective hypotheses?

Effective hypotheses can be found in various fields. For example, in social sciences: 'If social media usage increases, then levels of anxiety among teenagers will increase.' In natural sciences: 'If the temperature of water increases, then the solubility of salt will increase.'

How can hypotheses be evaluated and refined?

Hypotheses can be evaluated and refined through peer review and feedback, iterative refinement, and alignment with the overall research design. This process helps in improving the clarity and testability of the hypothesis.

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Rethinking the Virtuous Circle Hypothesis on Social Media: Subjective versus Objective Knowledge and Political Participation

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Sangwon Lee, Trevor Diehl, Sebastián Valenzuela, Rethinking the Virtuous Circle Hypothesis on Social Media: Subjective versus Objective Knowledge and Political Participation, Human Communication Research , Volume 48, Issue 1, January 2022, Pages 57–87, https://doi.org/10.1093/hcr/hqab014

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Despite early promise, scholarship has shown little empirical evidence of learning from the news on social media. At the same time, scholars have documented the problem of information ‘snacking’ and information quality on these platforms. These parallel trends in the literature challenge long-held assumptions about the pro-social effects of news consumption and political participation. We argue that reliance on social media for news does not contribute to people’s real level of political knowledge (objective knowledge), but instead only influences people’s impression of being informed (subjective knowledge). Subjective knowledge is just as important for driving political participation, a potentially troubling trend given the nature of news consumption on social media. We test this expectation with panel survey data from the 2018 U.S. midterm elections. Two path model specifications (fixed effects and autoregressive) support our theoretical model. Implications for the study of the ‘dark side’ of social media and democracy are discussed.

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FEATURE 17 February 2017

A hypothesis-driven approach to social media insight

Bronwen Morgan

Data analytics Features Media Social media UK

Speaking at yesterday’s Social Media Research Summit, organised by the Market Research Society (MRS), Pulsar’s co-founder and vice president of product and research, Francesco D'Orazio, demonstrated how to use social media to validate a specific research hypothesis. 

Social media data has transformed the scope of research. The availability of 11 years of Twitter data at the touch of a button is just the tip of the iceberg, said D'Orazio, who went on to extol the benefits of both the granularity of publicly available data (Twitter and Instagram) and the aggregated nature of Facebook and LinkedIn data. 

But the sheer quantity of interactions can make analysis challenging, which is why D'Orazio believes in the value of an emerging research approach: using social data as a tool to validate specific research hypotheses, rather than as an exploratory tool. 

The traditional ‘emergence’ approach, said D'Orazio, relies on "seeing what crops up" and is based on keywords and stories. The ‘hypothesis’ approach involves framing data: looking at it through the lens of a specific question. In short, the hypothesis approach shifts much of the analysis to before data collection, rather than afterwards. 

The key advantages of this approach are as follows: 

• Keeps the data collection focused and reduces ‘noise'
• Makes analysis faster, more structured and standardised
• Makes it easier to replicate results across teams
• Makes it easier to integrate social data with third party sources such as surveys

D'Orazio took the audience through the process of this method: from client brief, to hypothesis, to data query, to insights. 

In order to move from the client brief to a research hypothesis, the researcher must break the brief down into three elements: What is the business objective? What is the target audience? What are we trying to understand? 

This is then further broken down into two elements: Who is the audience you're trying to reach? And what type of behaviour and moments should be investigated? 

The researcher can then create a hypothesis for each of these elements that can then be investigated in the data. The more focused this is, the better, said D'Orazio. It should be considered as a frame for looking at the data, rather than simply a theory to be validated. 

The next step is to transform the hypothesis into a study definition. A hypothesis will contain – and be related to – a number of elements: language; behaviours; attitudes; moments and occasions.

Transforming the hypothesis means defining the ‘signals’ to look out for, such as audience demographics and a list of terms (and sub-terms) to look out for.

For example, if you're investigating fast food consumption among UK/US millennials, a hypothesis could be that the UK/US millennial audience buy into authenticity and not the fast casual proposition. The terms to look out for could then be: ingredients, pairings, sustainability, price, health, occasions, behaviours and quality. Within quality, for example, there are terms to look out for such as: premium, chef, better, best, amazing, etc.

The last stage is to test the study outputs, including comparing the results across demographics for context, looking at the language used and how it compares to the hypothesis. 

This can offer insight into how consumers talk about a category, including how terms are conflated or distinguished, what behaviours and attitudes relate to the category (for different demographics), and what types of conversations people have. 

This can either validate the original hypothesis, disprove it or drive completely new insight, D'Orazio explained. 

Kathy Doering

8 years ago

Wow! What an excellent, insightful article. With social media monitoring softwares changing all the time, we are able to do more and more with social data and weed out the noise. Location based monitoring and digital image searching are both available and are a great additional resources for researchers and marketers.

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How to Write a Research Hypothesis: Good & Bad Examples

What is a research hypothesis?

A research hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. Hypotheses are sometimes called “educated guesses”, but they are in fact (or let’s say they should be) based on previous observations, existing theories, scientific evidence, and logic. A research hypothesis is also not a prediction—rather, predictions are ( should be) based on clearly formulated hypotheses. For example, “We tested the hypothesis that KLF2 knockout mice would show deficiencies in heart development” is an assumption or prediction, not a hypothesis. 

The research hypothesis at the basis of this prediction is “the product of the KLF2 gene is involved in the development of the cardiovascular system in mice”—and this hypothesis is probably (hopefully) based on a clear observation, such as that mice with low levels of Kruppel-like factor 2 (which KLF2 codes for) seem to have heart problems. From this hypothesis, you can derive the idea that a mouse in which this particular gene does not function cannot develop a normal cardiovascular system, and then make the prediction that we started with. 

What is the difference between a hypothesis and a prediction?

You might think that these are very subtle differences, and you will certainly come across many publications that do not contain an actual hypothesis or do not make these distinctions correctly. But considering that the formulation and testing of hypotheses is an integral part of the scientific method, it is good to be aware of the concepts underlying this approach. The two hallmarks of a scientific hypothesis are falsifiability (an evaluation standard that was introduced by the philosopher of science Karl Popper in 1934) and testability —if you cannot use experiments or data to decide whether an idea is true or false, then it is not a hypothesis (or at least a very bad one).

So, in a nutshell, you (1) look at existing evidence/theories, (2) come up with a hypothesis, (3) make a prediction that allows you to (4) design an experiment or data analysis to test it, and (5) come to a conclusion. Of course, not all studies have hypotheses (there is also exploratory or hypothesis-generating research), and you do not necessarily have to state your hypothesis as such in your paper. 

But for the sake of understanding the principles of the scientific method, let’s first take a closer look at the different types of hypotheses that research articles refer to and then give you a step-by-step guide for how to formulate a strong hypothesis for your own paper.

Types of Research Hypotheses

Hypotheses can be simple , which means they describe the relationship between one single independent variable (the one you observe variations in or plan to manipulate) and one single dependent variable (the one you expect to be affected by the variations/manipulation). If there are more variables on either side, you are dealing with a complex hypothesis. You can also distinguish hypotheses according to the kind of relationship between the variables you are interested in (e.g., causal or associative ). But apart from these variations, we are usually interested in what is called the “alternative hypothesis” and, in contrast to that, the “null hypothesis”. If you think these two should be listed the other way round, then you are right, logically speaking—the alternative should surely come second. However, since this is the hypothesis we (as researchers) are usually interested in, let’s start from there.

Alternative Hypothesis

If you predict a relationship between two variables in your study, then the research hypothesis that you formulate to describe that relationship is your alternative hypothesis (usually H1 in statistical terms). The goal of your hypothesis testing is thus to demonstrate that there is sufficient evidence that supports the alternative hypothesis, rather than evidence for the possibility that there is no such relationship. The alternative hypothesis is usually the research hypothesis of a study and is based on the literature, previous observations, and widely known theories. 

Null Hypothesis

The hypothesis that describes the other possible outcome, that is, that your variables are not related, is the null hypothesis ( H0 ). Based on your findings, you choose between the two hypotheses—usually that means that if your prediction was correct, you reject the null hypothesis and accept the alternative. Make sure, however, that you are not getting lost at this step of the thinking process: If your prediction is that there will be no difference or change, then you are trying to find support for the null hypothesis and reject H1. 

Directional Hypothesis

While the null hypothesis is obviously “static”, the alternative hypothesis can specify a direction for the observed relationship between variables—for example, that mice with higher expression levels of a certain protein are more active than those with lower levels. This is then called a one-tailed hypothesis. 

Another example for a directional one-tailed alternative hypothesis would be that 

H1: Attending private classes before important exams has a positive effect on performance. 

Your null hypothesis would then be that

H0: Attending private classes before important exams has no/a negative effect on performance.

Nondirectional Hypothesis

A nondirectional hypothesis does not specify the direction of the potentially observed effect, only that there is a relationship between the studied variables—this is called a two-tailed hypothesis. For instance, if you are studying a new drug that has shown some effects on pathways involved in a certain condition (e.g., anxiety) in vitro in the lab, but you can’t say for sure whether it will have the same effects in an animal model or maybe induce other/side effects that you can’t predict and potentially increase anxiety levels instead, you could state the two hypotheses like this:

H1: The only lab-tested drug (somehow) affects anxiety levels in an anxiety mouse model.

You then test this nondirectional alternative hypothesis against the null hypothesis:

H0: The only lab-tested drug has no effect on anxiety levels in an anxiety mouse model.

How to Write a Hypothesis for a Research Paper

Now that we understand the important distinctions between different kinds of research hypotheses, let’s look at a simple process of how to write a hypothesis.

Writing a Hypothesis Step:1

Ask a question, based on earlier research. Research always starts with a question, but one that takes into account what is already known about a topic or phenomenon. For example, if you are interested in whether people who have pets are happier than those who don’t, do a literature search and find out what has already been demonstrated. You will probably realize that yes, there is quite a bit of research that shows a relationship between happiness and owning a pet—and even studies that show that owning a dog is more beneficial than owning a cat ! Let’s say you are so intrigued by this finding that you wonder: 

What is it that makes dog owners even happier than cat owners? 

Let’s move on to Step 2 and find an answer to that question.

Writing a Hypothesis Step 2:

Formulate a strong hypothesis by answering your own question. Again, you don’t want to make things up, take unicorns into account, or repeat/ignore what has already been done. Looking at the dog-vs-cat papers your literature search returned, you see that most studies are based on self-report questionnaires on personality traits, mental health, and life satisfaction. What you don’t find is any data on actual (mental or physical) health measures, and no experiments. You therefore decide to make a bold claim come up with the carefully thought-through hypothesis that it’s maybe the lifestyle of the dog owners, which includes walking their dog several times per day, engaging in fun and healthy activities such as agility competitions, and taking them on trips, that gives them that extra boost in happiness. You could therefore answer your question in the following way:

Dog owners are happier than cat owners because of the dog-related activities they engage in.

Now you have to verify that your hypothesis fulfills the two requirements we introduced at the beginning of this resource article: falsifiability and testability . If it can’t be wrong and can’t be tested, it’s not a hypothesis. We are lucky, however, because yes, we can test whether owning a dog but not engaging in any of those activities leads to lower levels of happiness or well-being than owning a dog and playing and running around with them or taking them on trips.  

Writing a Hypothesis Step 3:

Make your predictions and define your variables. We have verified that we can test our hypothesis, but now we have to define all the relevant variables, design our experiment or data analysis, and make precise predictions. You could, for example, decide to study dog owners (not surprising at this point), let them fill in questionnaires about their lifestyle as well as their life satisfaction (as other studies did), and then compare two groups of active and inactive dog owners. Alternatively, if you want to go beyond the data that earlier studies produced and analyzed and directly manipulate the activity level of your dog owners to study the effect of that manipulation, you could invite them to your lab, select groups of participants with similar lifestyles, make them change their lifestyle (e.g., couch potato dog owners start agility classes, very active ones have to refrain from any fun activities for a certain period of time) and assess their happiness levels before and after the intervention. In both cases, your independent variable would be “ level of engagement in fun activities with dog” and your dependent variable would be happiness or well-being . 

Examples of a Good and Bad Hypothesis

Let’s look at a few examples of good and bad hypotheses to get you started.

Good Hypothesis Examples

Bad Hypothesis Examples

Tips for Writing a Research Hypothesis

If you understood the distinction between a hypothesis and a prediction we made at the beginning of this article, then you will have no problem formulating your hypotheses and predictions correctly. To refresh your memory: We have to (1) look at existing evidence, (2) come up with a hypothesis, (3) make a prediction, and (4) design an experiment. For example, you could summarize your dog/happiness study like this:

(1) While research suggests that dog owners are happier than cat owners, there are no reports on what factors drive this difference. (2) We hypothesized that it is the fun activities that many dog owners (but very few cat owners) engage in with their pets that increases their happiness levels. (3) We thus predicted that preventing very active dog owners from engaging in such activities for some time and making very inactive dog owners take up such activities would lead to an increase and decrease in their overall self-ratings of happiness, respectively. (4) To test this, we invited dog owners into our lab, assessed their mental and emotional well-being through questionnaires, and then assigned them to an “active” and an “inactive” group, depending on… 

Note that you use “we hypothesize” only for your hypothesis, not for your experimental prediction, and “would” or “if – then” only for your prediction, not your hypothesis. A hypothesis that states that something “would” affect something else sounds as if you don’t have enough confidence to make a clear statement—in which case you can’t expect your readers to believe in your research either. Write in the present tense, don’t use modal verbs that express varying degrees of certainty (such as may, might, or could ), and remember that you are not drawing a conclusion while trying not to exaggerate but making a clear statement that you then, in a way, try to disprove . And if that happens, that is not something to fear but an important part of the scientific process.

Similarly, don’t use “we hypothesize” when you explain the implications of your research or make predictions in the conclusion section of your manuscript, since these are clearly not hypotheses in the true sense of the word. As we said earlier, you will find that many authors of academic articles do not seem to care too much about these rather subtle distinctions, but thinking very clearly about your own research will not only help you write better but also ensure that even that infamous Reviewer 2 will find fewer reasons to nitpick about your manuscript. 

Perfect Your Manuscript With Professional Editing

Now that you know how to write a strong research hypothesis for your research paper, you might be interested in our free AI Proofreader , Wordvice AI, which finds and fixes errors in grammar, punctuation, and word choice in academic texts. Or if you are interested in human proofreading , check out our English editing services , including research paper editing and manuscript editing .

On the Wordvice academic resources website , you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.

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How to Win Friends and Influence Your Audience: 10 Theories to Know For Greater Persuasion

Former VP of Marketing @ Buffer

What are we really talking about when we’re talking about conversions ?

Persuasion, right? Influence.

When we talk about conversions , we are—most of the time—discussing ways we can be more persuasive, more influential . We’re interested in meeting the needs of customers, fans, and followers and doing so in a way that truly speaks to them.

So how can you persuade—i.e., convert—better?

Perhaps not surprisingly, the hacks for conversion and persuasion begin with psychology. Understanding why someone clicks or why they retweet requires you to look at the way the person is wired, the way we are all wired. To understand persuasion and social media influence , to get at the heart of conversion and likes, it helps to understand how your audience thinks and feels. Here’s a primer.

The psychological theories of influence and persuasion

One of my favorite places to learn about psychological theories is Dave Straker’s Changing Minds website, which is full of theories written in layman’s terms, organized neatly into specific categories and clusters for easy reference. One of those categories is persuasion, and Straker lists 10 different psychological theories that deal with how to influence others.

Here is a brief snapshot of each of the 10 theories, many of which might sound familiar to you—either because you’ve employed them in the past or because you’ve had others try them on you.  For more information on any of these, click through the links to see Changing Minds’ cited research and examples.

1. Amplification Hypothesis

When you express with certainty a particular attitude, that attitude hardens. The opposite is true as well: Expressing uncertainty softens the attitude.

2. Conversion Theory

The minority in a group can have a disproportionate effect on influencing those in the majority.  Typically, those in the majority who are most susceptible are the ones who may have joined because it was easy to do so or who felt there were no alternatives. Consistent, confident minority voices are most effective.

3. Information Manipulation Theory

This theory involves a persuasive person deliberately breaking one of the four conversational maxims . These are the four:

• Quantity : Information is complete and full.
• Quality : Information is truthful and accurate.
• Relation : Information is relevant to the conversation.
• Manner : Information is expressed in an easy-to-understand way and non-verbal actions support the tone of the statement

You can be influenced by stimuli that affect how you perceive short-term thoughts and actions . Here’s a really smart example from Changing Minds:

A stage magician says ‘try’ and ‘cycle’ in separate sentences in priming a person to think later of the word ‘tricycle’.

5. Reciprocity Norm

A common social norm, reciprocity involves our obligation to return favors done by others .

6. Scarcity Principle

You want what is in short supply . This desire increases as you anticipate the regret you might have if you miss out by not acting fast enough.

(Note the “Just for Today” text in the example email below.)

7. Sleeper Effect

Persuasive messages tend to decrease in persuasiveness over time, except messages from low-credibility sources . Messages that start out with low persuasion gain persuasion as our minds slowly disassociate the source from the material (i.e., a presumably sleazy car salesman and his advice on what car is best).

8. Social Influence

We are influenced strongly by others based on how we perceive our relationship to the influencer . For example, social proof on web copy is persuasive if the testimonials and recommendations are from authoritative sources, big brands, or peers.

9. Yale Attitude Change Approach

This approach, based on multiple years of research by Yale University, found a number of factors in persuasive speech, including being a credible, attractive speaker ; when it’s important to first or go last; and the ideal demographics to target.

10. Ultimate Terms

Certain words carry more power than others. This theory breaks persuasive words into three categories:

• God terms: those words that carry blessings or demand obedience/sacrifice. e.g, progress, value
• Devil terms: those terms that are despised and evoke disgust. e.g., fascist, pedophile
• Charismatic terms: those terms that are intangible, less observable than either God or Devil terms. e.g., freedom, contribution

(We’ve written before about the power of specific words , including the five most persuasive words in the English language: You, Because, Free, Instantly, and New.)

You might consider these 10 theories the building blocks of the persuasive techniques explained below. With this foundation of psychology in place, let’s move on to some applications of these theories in your social media marketing, website planning, and content creation.

How to write for what we all crave

We all know how important food, water, shelter, and warmth are to survival. Any ideas what’s next most important?

The Hierarchy of Needs pyramid, proposed by psychologist Abraham Maslow in the 1940s, shows the advancing scale of how our needs lay out on the path to fulfillment, creativity, and the pursuit of what we love most. The version of the pyramid you see below ( shared by the Doorway Project ) shows the five different layers of needs.

The three steps in between the physiological needs and the fulfillment needs are where marketing most directly applies.

In Maslow’s pyramid, the descriptions for these needs don’t exactly have a marketing perspective to them, so it requires a little creativity to see how you can tailor your message to fit these needs. Christine Comaford, an author and expert on the subject of persuasion, has found safety, belonging, and esteem to have incredible value for our everyday work and our creative lives :

Without these three essential keys a person cannot perform, innovate, be emotionally engaged, agree, or move forward … The more we have of (these three keys) the greater the success of the company, the relationship, the family, the team, the individual.

Her experience has helped her hone three phrases that are key for influence and persuasion and for creating this sense of safety, belonging, and mattering that we all need. Here they are:

• “What if.” This phrase removes ego from the discussion and creates a safe environment for curiosity and brainstorming.
• “I need your help.” This flips the roles of dominant and subordinate, engaging the other person and providing a transfer of power.
• “Would it be helpful if.” This phrase shifts the focus from the problem to the solution.

Here’s an example from Nick Eubanks of SEO Nick who uses the phrase “I Need Your Help” directly in the subject line of an email. (Come to think of it, each of these three would be fun to try as email subject lines .)

How to win friends and influence your audience

When you talk about influencing people, our ears perk up at Buffer. Our company culture and values are based on a book by Dale Carnegie called How to Win Friends and Influence People. The advice from Christine Comaford above has that familiar ring of Carnegie to it. Remove your ego. Default to happiness and positivity. Be welcoming to others.

In a lot of ways, a discussion on persuasion and influence could begin and end with Carnegie’s book. Here is just a segment of the book’s table of contents, filled with ideas on kindness, generosity, and partnership. (Carnegie would probably dislike that I’m having you read just the table of contents—he advised readers to read each chapter of his book multiple times.)

Win people to your way of thinking

• The only way to get the best of an argument is to avoid it.
• Show respect for the other person’s opinions. Never say, “You’re wrong.”
• If you are wrong, admit it quickly and emphatically.
• Begin in a friendly way.
• Get the other person saying “yes, yes” immediately.
• Let the other person do a great deal of the talking.
• Let the other person feel that the idea is his or hers.
• Try honestly to see things from the other person’s point of view.
• Be sympathetic with the other person’s ideas and desires.
• Appeal to the nobler motives.
• Dramatize your ideas.
• Throw down a challenge.

Isn’t that great stuff?

We aim to include as many Carnegie principles as we can in the way that we communicate in emails, in comments, and of course on social media. Here are some examples from Twitter of how our Happiness Heroes practice friendliness, sympathy, and seeing things from someone else’s perspective.

We’re not the only ones who love Carnegie’s book, either. An article on Copyblogger by Andrew Schrage and Brian Spero broke down the specific ways that you can grow an audience and market your content based on Carnegie’s principles. The full article contains 10 tips . Here are two of my favorites:

Avoid misleading headlines. A staple of Carnegie’s proven methods involves recognizing the importance of others. Too often we forget this and treat online audiences as easily manipulated rubes.

Instead of writing clickbait headlines that aim to coerce, it’s better to practice clickable headlines that work for more virtuous reasons . Digg.com aggregates the top stories from the web and delivers them with headlines that are informative and clever without being manipulative.

The second Carnegie tip from Copyblogger goes like this:

Save people money. In “How to Win Friends,” we learn the importance of talking about what people want and showing them how to get it.

In other words, talk about benefits instead of features .

Here is a screengrab from the landing page of Keen.io , an analytics service for developers. Instead of explaining the features of the product—the APIs and the SDKS—Keen talks about benefits.

While not as overt as the analysis on Copyblogger, Minda Zeltin, president of American Society of Journalists and Authors, wrote on Inc.com about her own experiences with persuasion and influence, referencing indirectly a lot of the attitudes expressed by Carnegie.

Here are a few specific examples that Zeltin cites that deal directly with how you speak to others:

Michael Hyatt nails these elements of persuasive speech in his communication with email subscribers. In addition to a few emails I’ve received apologizing for broken links or other mistakes, Hyatt is also so kind and generous in the way he approaches his conversations. Here is an email that includes both a big thank you and some praise.

The persuasion slide: How an influential nudge leads to conversion

Here’s a fun way to look at persuasion: as a playground slide.

The idea comes from Roger Dooley of the blog Neuromarketing who uses the variables of a person on a slide to show how different factors affect the outcome of influence. Here’s the graphic he created to explain the idea:

Essentially, here’s how it works :

You give a customer a nudge (a tweet, a blog post, a phone call, an ad).

Gravity , that customer’s internal motivations, help move the customer down the slide.

Additional motivation that you provide (the angle of the slide) can serve to enhance the gravity. If a customer has low internal motivation, it will take a steeper angle to get him or her down the slide.

Friction , seen here as the difficulty (real and perceived) in converting, causes the slide to slow down to varying degrees.

The nudge could be most anything persuasive, for example a couple of psychological theories that we outlined above. Amplification could mean that the customer is further cementing his values and attitudes as he propels down the slide. Social proof could be a stronger push down the slide, resulting in a faster conversion.

Robert Cialdini’s 6 principles of persuasion

Shane Parrish of Farnam Street reads a lot of books— up to 14 each month –so it means something when he picks Robert Cialdini’s Influence: The Psychology of Persuasion as one of the most important books he’s read . In the book, Cialdini outlines six principles of persuasion, most of which will likely sound a bit familiar based on our previous discussion on psychology.

Do any of those sound familiar? Put another way, Cialdini’s list could look like this:

• Reciprocation, i.e. Reciprocity Norm
• Consistency,  i.e. Amplification Hypothesis
• Social proof, i.e. Social Influence
• Liking, i.e. Social Influence (again)
• Authority, i.e. Yale Attitude Change Approach
• Scarcity, i.e. Scarcity Principle

One of the common threads from Cialdini’s list is that of social. The principles of liking, authority, and social proof all deal with relationships with others: We are persuaded by those we like, by those whom we deem to be authority figures, and by the general population. Here are a few unique applications of these, as told by Cialdini and Parrish :

One way people exploit this is to find ways to make themselves like you. Do you like golf? Me too. Do you like football? Me too. Although often these are genuine, sometimes they’re not.

Liking is similar enough to consistency that it bears pointing out the difference here. Someone might say, “Do you like having more visitors to your blog?” They aren’t necessarily looking for a connection with you (as in Liking) but rather they’re seeking Consistency. Of course you’ll say yes, and in theory, you’ll have a harder time backing off that statement when you are pitched a product or service later.

Something as simple as informing your audience of your credentials before you speak, for example, increases the odds you will persuade the audience.

Noah Kagan does this for the each guest post he publishes at OK Dork . He writes a quick intro on how he made the connection with the guest writer and all the amazing credentials the guest writer has.

Social proof

People will more likely say yes when they see other people doing it too. Social poof is not all bad. It’s one of the main ways we learn in life.

Basecamp has a great example of social proof on their website, showing the wide variety of respected clients that use the product—and doing so in a fun, approachable way.

Two others that are worth pointing out are consistency and scarcity.

Personally, consistency is the one I find myself most susceptible to, and I identify a lot with how Parrish describes the effect: “If you ask people to state their priorities and goals and then align your proposals with that in mind, you make it harder for people to say no.” really hit home for me. Parrish connects this to the IKEA effect , the way you love your IKEA furniture because you’re invested in it from building it yourself.

As for scarcity, Visual Website Optimizer wrote an extensive post on all the different ways you can use scarcity to increase e-commerce sales. Have you noticed that Amazon tells people there are only a certain number of products left? That’s scarcity at play.

Hooks: Psychology in action in your copy and on your site

Throughout this post, I’ve tried to highlight some good examples of the psychology of persuasion as it exists on the web. It’s great to know the theories; it’s also helpful to see the techniques and applications. Bushra Azhar, a persuasion strategist and founder of The Persuasion Revolution, wrote down several of her techniques that she has used to great effect in creating persuasive copy. Here is a sampling of the ways she’s used to invoke positive emotions in website visitors.

Disrupt then reframe

You can disrupt routine thought processes by mixing around the words and visuals that a user is used to seeing then reframing your pitch while they’re still figuring out the disruption. Researchers tested this technique by pitching a product as costing $3.00 versus 300 pennies; the penny pitch was the clear winner.

A unique implementation of this is on TeuxDeux’s pricing page. Instead of standard names for their pricing tiers, TeuxDeux went with a disruption technique with the copy and then reframed the pitch with the pricing info below.

The key to good storytelling

We mentioned above the theory about ultimate words, and we’ve written recently about the power of storytelling in your content. Azhar points out that a step beyond storytelling is making sure that you are telling the right story. She references the book Made to Stick , which talks about the three stickiest and most memorable story plots.

1. The Challenge Plot: A story of the underdog, rags to riches or sheer willpower triumphing over adversity 2. The Connection Plot: A story about people who develop a relationship that bridges a gap, whether racial, class, ethnic, religious, demographic or otherwise; think of the film The Blind Side 3. The Creativity Plot: A story that involves someone making a mental breakthrough, solving a long-standing puzzle or attacking a problem in an innovative way

The Groove HQ blog regularly starts blog posts with a storytelling element, often using variations on The Creativity Plot to hook readers and give that nudge down the persuasion slide.

Opportunities for persuasion

By now, I’m sure you can see just how much psychology is involved in the art of persuasion. By extension, you can also see psychology in the social media messages and marketing tactics of some influential brands.

When it comes to applying the principles of persuasive psychology, here are a few places you can start:

• Your calls-to-action
• Your headlines
• Your tweets and updates
• Your emails
• Your product descriptions

Almost anywhere that you have words or visuals—anywhere that you create or manage content—you can turn into an opportunity for persuasion.

What places on your website and in your social media marketing have you used psychological persuasion? Which of these theories do you recognize, either in your own marketing or in the marketing of others? I’d love to take this conversation further in the comments.

P.S. If you liked this post, you might also like Why We Buy Into Ideas: How to Convince Others of Our Thoughts and 8 Winning Headline Strategies and the Psychology Behind Them .

Image credits: Dave Chapman , Doorway Project , Neuromarketing , Little Big Details.

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Theories of Social Media: Philosophical Foundations

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Social media use and social connectedness among adolescents in the United Kingdom: a qualitative exploration of displacement and stimulation

Lizzy winstone.

1 Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN UK

2 NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, BS8 2BN UK

Claire M. A. Haworth

3 School of Psychological Science, University of Bristol, Bristol, BS8 1TU UK

4 The Alan Turing Institute, British Library, London, NW1 2DB UK

Judi Kidger

Associated data.

The qualitative datasets generated and analysed during the current study are not publicly available due to the data containing information that could compromise research participant privacy but are available from the corresponding author on reasonable request.

Connectedness to family and peers is a key determinant of adolescent mental health. Existing research examining associations between social media use and social connectedness has been largely quantitative and has focused primarily on loneliness, or on specific aspects of peer relationships. In this qualitative study we use the displacement hypothesis and the stimulation hypothesis as competing theoretical lenses through which we examine the complex relationship between social media use and feelings of connectedness to family and peers.

In-depth paired and individual interviews were conducted with twenty-four 13–14-year-olds in two inner-city English secondary schools. Interviews were transcribed verbatim, coded and thematically analysed.

Analysis identified four themes: (i) ‘Displacement of face-to-face socialising’ (ii) ‘Social obligations’ (iii) ‘(Mis)Trust’ and (iv) ‘Personal and group identity’. Results indicated stronger support for the stimulation hypothesis than the displacement hypothesis. We found evidence of a complex set of reciprocal and circular relationships between social media use and connectedness consistent with a ‘rich-get-richer’ and a ‘poor-get-poorer’ effect for family and peer connectedness – and a ‘poor-get-richer’ effect in peer connectedness for those who find face-to-face interactions difficult.

Our findings suggest that parents should take a measured approach to social media use, providing clear guidance, promoting trust and responsible time management, and acknowledging the role of social media in making connections. Understanding and sharing in online experiences is likely to promote social connectedness. Supporting young people to negotiate breathing space in online interactions and prioritising trust over availability in peer relationships may optimise the role of social media in promoting peer connectedness.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11802-9.

Introduction

Social connectedness is defined as feelings of belonging and closeness to others, as well as satisfaction with relationships and perceived support and opportunities for self-disclosure of personal information. It comprises different domains (peer, school, family and community/ neighbourhood) and is a key social determinant of adolescent mental health and well-being [ 1 – 3 ]. Family connectedness in particular has been found to buffer the negative effects of bullying and to be related to lower risk for suicide-related outcomes and depressive symptoms [ 3 , 4 ].

Social media use (SMU) is thought to have both positive and negative influences on the lives of young people, for whom it has become an integral part of daily life [ 5 ]. In 2018, 80% of 14-year-olds in the United Kingdom (UK) had a profile on a social media or messaging app [ 6 ]. For the purposes of this study, we include within social media social network sites as defined by boyd and Ellison [ 7 ], in addition to web-based messaging and microblogging services (such as WhatsApp and Tumblr) and social video platforms (such as YouTube). SMU has various functions, with users typically seeking entertainment, communication, inspiration and information. The use of social media to engage with others, either through direct communication or through the publication or consumption of content and its associated feedback, makes it an inherently social part of adolescence [ 8 ]. As such, SMU may have important implications for increasing connectedness with individuals and groups [ 9 ]. However, concerns have been raised by parents about screen-time interfering with other activities that may also be beneficial to connectedness [ 10 ], such as schoolwork, extra-curricular activities and engaging with others face-to-face. Through these competing processes of stimulation and displacement, SMU may simultaneously enhance and undermine social connectedness in adolescence [ 9 ].

The displacement and stimulation hypotheses

The displacement hypothesis was formulated on the basis of internet use rather than social media specifically [ 11 ]. The theory of displacement is two-fold, regarding both time displacement and displacement of strong social ties with weak ones. Use of the internet for entertainment purposes – as a solitary, socially disengaged activity comparable to passive consumption of social media content without active engagement – is thought to displace time spent socialising with others offline, subsequently undermining social connectedness [ 11 , 12 ]. Where used for communication purposes, online engagement and expansion of social networks were thought to be primarily with weak ties rather than with close family and friends, and as such, of little benefit to psychosocial well-being [ 11 , 13 ].

In line with this hypothesis, previous research has found that SMU is associated with increases in bridging but not bonding social capital, whereby vast expansion of social networks made possible through SMU enhances the number of weak social ties rather than improving relationships with close friends and family [ 5 ]. SMU may also displace time spent on other activities beneficial to well-being, including physical exercise and sleep [ 14 , 15 ]. With regards to family connectedness, an intensive longitudinal experience sampling study found little evidence that time spent using digital technology displaced time spent engaging offline with parents or resulted in problematic parent-adolescent offline interactions [ 16 ].

Evidence also exists in support of an opposing theory, the stimulation hypothesis, whereby SMU enhances the user’s existing social resources through increased contact and maintenance of relationships [ 17 , 18 ]. In direct contradiction to the displacement hypothesis (whereby strong social ties are displaced with weak ones) it has been suggested that adolescents are increasingly using social media to enhance the quality of existing friendships rather than seeking out new connections, leading to beneficial impacts on social connectedness and social and emotional support [ 17 ].

One study directly compared the two competing hypotheses and found that, rather than displacing time spent offline with friends, use of instant messenger was positively related to face-to-face socialising, in turn predicting better friendship quality and well-being [ 19 ]. This effect was specific to using instant messenger to communicate with friends and did not apply to use of chat rooms (primarily with strangers). The authors suggested that features of online communication – including asynchronous responding and absence of nonverbal cues or responses –could lower social inhibition and encourage sharing of personal information. These intimate self-disclosures can be beneficial to well-being and peer connectedness through enhancing feelings of support and trust [ 20 , 21 ].

Using experience sampling methodology, researchers have explored fluctuations in adolescents’ use of Instagram, Snapchat and WhatsApp with and without close friends [ 8 ]. Findings illustrated the complexity of the relationship between SMU and friendship closeness, with substantial differences at the within- and between-person level. Those who used Instagram or WhatsApp in the previous hour (whether with or without close friends) reported feeling slightly less close to close friends, however, those with a higher average frequency across a three-week period felt closer to their friends than those with less frequent use. Snapchat use was not found to be related to friendship closeness at either the within or between person level [ 8 ]. These findings were echoed in a study showing evidence for the displacement hypothesis at the within-person level – with increases in smartphone communication on a particular day reducing face-to-face interaction for a given individual – but not the between-person level – with no discernible difference in the level of face-to-face interaction for more or less prolific online communicators [ 22 ].

There is also evidence to suggest the relationship with SMU may be curvilinear, with only excessive levels of SMU found to be associated with lower levels of social capital [ 20 , 23 ] or poorer psychosocial functioning [ 24 ]. In a longitudinal study of adolescents in Belgium [ 23 ], Wang et al. found that low to moderate levels of active public Facebook use (that is broadcasting content publicly but not direct messaging with others) were associated with decreased loneliness over time, supporting the stimulation hypothesis. However, higher levels of broadcasting were associated with increased loneliness over time, indicating support for the displacement hypothesis. This indicates that rather than being mutually exclusive theories, both the stimulation and displacement hypotheses may be possible, depending on both the amount and type of SMU [ 17 ].

Objectives of the current study

Most existing research examining the displacement and stimulation hypotheses has been quantitative and has focused primarily on peer connectedness. Qualitative research, and research exploring the relationship between adolescent SMU and family connectedness is scarce. This qualitative study aimed to examine the relationship between SMU and social connectedness (encompassing peers and family) through the experiences and perspectives of a sample of 13–14-year-olds in south-west England.

Participants

Thirteen interviews were conducted with 24 Year 9 students aged 13–14 years (19 girls and five boys) in February–March 2020. Interviews took place at two English secondary schools in inner-city locations. One was in a particularly deprived area with an ethnically diverse and lower socio-economic status student population (measured by the proportion of students eligible for free school meals). The other was a single sex girls’ school with a higher-than-average socio-economic status population. Heads of Year 9 in each school were asked to advertise the study to all classes in the year group, with participant information sheets provided. The information sheets encouraged students with a range of social media experiences to take part, including those who considered themselves to be non-users. Two participants presented themselves as non-users of social media, describing their use of YouTube solely for entertainment purposes. Students volunteered to take part and all volunteers were selected for interview providing they returned signed parental consent forms by a cut-off date. In advance of the interviews, participants indicated on consent forms their preference for participation in an individual or paired interview with a friend (Table  1 ). Participants received a £10 Amazon voucher by way of thanks.

Interview format overview

Design and procedure

Interviews were all conducted face-to-face by LW. LW is a female PhD student with some previous experience of conducting in-depth interviews with adults, and is trained in qualitative data analysis and conducting research with young people. JK oversaw the process and is a female academic with extensive qualitative research experience. The interviews were audio recorded, took place at school during lesson time and lasted between 45 min and an hour. A topic guide (available in Additional file  1 ) was used to ensure consistency in covering a number of core areas for discussion, including typical apps and activities used, family and school rules regarding SMU, online interactions with peers, family or strangers and SMU in those experiencing poor mental health. The guide was developed following consultation with a young people’s advisory board – a group of 11–18-year-olds with experience in advising on the design of health-related research materials. The group provided input into issues they felt most important relating to SMU and mental health. Flexibility in the topic guide allowed interview participants to take the conversation in any direction they felt to be relevant to the broad issue of social media and mental health, reflecting on their own SMU as well as that of their peers. This flexibility was felt to be important in mitigating the impact of the adult researchers’ preconceptions about adolescent SMU, social connectedness and mental health, enabling openness to experiences recognised as meaningful by participants themselves.

Data analysis

An inductive, reflexive approach to thematic analysis was used from a critical realist (contextualist) perspective [ 25 ]. SMU is so intertwined with one’s experience and perceptions of interpersonal and intergroup relationships that it would not make sense to refer to there being an authentic truth or reality. However, as researchers aspiring to improve public mental health through recommendations to stakeholders, we need to acknowledge young people’s experiences and feelings as an external reality, whilst recognising the prisms through which these are encountered by young people and interpreted by ourselves [ 25 ]. We interpreted the data as adults who experienced adolescence in a time before social media existed and we reflected on this throughout the analytic process.

Notes were taken during and after each interview. These were not coded but used in reflection during analysis. The interviews were transcribed verbatim and imported into NVivo version 12 for coding by LW. Analysis was conducted primarily by LW, from the perspective of an adult using social media for direct communication with existing friends and family. LW acknowledges that her own experiences – both positive and negative – of SMU will unavoidably frame her interpretation of the data.

A systematic and inclusive coding process was adopted, with coding applied flexibly to include unexpected data [ 25 ]. Codes were both descriptive (e.g., ‘nothing to do’) and interpretative (e.g., ‘privacy concerns’). Following coding of the complete dataset, initial themes were constructed and reviewed iteratively when examined against each interview, with thematic boundaries altered as necessary. Further amendments were made where appropriate following group discussion between the authors to review both codes and themes. During the review process codes considered irrelevant to the research question (e.g., ‘apps’) were discarded or included within other codes where appropriate (e.g., ‘memories’ was encapsulated within ‘friendships’). Two previously separate themes – ‘keeping in touch’ and ‘time displacement’ were merged into ‘displacement of face-to-face socialising’. Once themes were developed, they were examined in relation to the displacement and stimulation hypotheses to see whether findings confirmed, contradicted, or developed these theories. Participants were not asked to provide feedback on the findings.

Four themes were identified through analysis of the qualitative interview data with regard to SMU and social connectedness. Table  2 provides an overview of these themes and sub-themes with key illustrative data extracts. Each sub-theme is discussed in turn, along with implications for displacement and stimulation theories. There were no systematic differences in opinions and experiences between participants from the two different schools or those interviewed individually compared to with others, so comparisons are not presented here.

Overview of themes, sub-themes and illustrative quotes

Displacement of face-to-face socialising

Elements of both displacement and stimulation were interwoven in discussions of online and offline socialising. Participants’ own SMU was sometimes felt to displace face-to-face social activities that promote feelings of connectedness. However, online peer interactions frequently took place when in-person socialising was not possible, helping to alleviate feelings of boredom and loneliness. Social network expansion was also highlighted as a key benefit of SMU, meeting new people, and maintaining contact with old friends outside of school and family members abroad.

Socialising with family

Several participants suggested that time spent socialising with family members would likely increase if they were to reduce their social media screen-time. Participant F5 spoke about recently breaking her phone and noted the positive impact it had on increasing time spent with her family.

Those participants who appeared to be minimal social media users reflected most on the importance of not ‘missing out’ on time with family (M3). Being with and ‘helping’ (M2) family was highlighted as a priority for these participants, with M2 suggesting that ‘talking to your family… is safer than talking on social media’. The strong family connectedness depicted by these participants appeared to have a protective effect against SMU displacing time spent together.

More frequently however, references to family connectedness and screen-time suggested increased SMU was a result rather than a cause of poor connectedness. Several participants alluded to their SMU at home as a means of reducing boredom or loneliness, because family members were not available to share meals or converse (F1, F2, M4, F6, F7, F12, F16). Some participants described family situations where disruption to home life, unsocial family dynamics or parents’ work patterns created time where they were left alone and turned to SMU because there was ‘nothing else to do’ (F1, F18, F19). F7 described sitting alone to eat dinner while using her phone and noted ‘…we just don’t do things as a family. It’s not social media, it’s just like, we just don’t do things.’

Consistent with the stimulation hypothesis, participants explained the benefits of communicating via social media to stay connected to family members who did not live close by, enhancing family connectedness beyond the nuclear family unit. This was felt to be particularly beneficial to those who would otherwise find the cost of overseas communication prohibitive. For some, this applied to one-to-one relationships with cousins of a similar age (F8). For others, group chats on social media enabled geographically disparate family members to come together as one to catch up or celebrate special occasions (F3).

Rather than displacing time spent socialising face-to-face with family, these comments showed how SMU was an important means of maintaining social interaction when in-person contact was not possible.

Socialising with friends

Across the sample, there were diverging opinions as to whether there was a difference between online and face-to-face socialising. In line with the displacement hypothesis, some found socialising through social media to be less rewarding than face-to-face, pointing particularly to the more genuine feel to in-person interactions where ‘you’ll see how they really are in person’ (F4) and can ‘gauge more’ (F6). Others gave opinions more aligned with the stimulation hypothesis, whereby online socialising facilitated offline interaction when they felt their own personalities to be ‘shy’ or socially ‘awkward’ (F6) – a social compensation effect [ 26 ]. As participant F10 put it, ‘I’m better friends with people because I’ve spoken to them more online and therefore in real life, we’re better friends. I wouldn’t say it’s different, no’.

As with family interactions, some participants pointed to the possibility of excessive SMU displacing time spent socialising in person with friends, leading some young people to ‘distance themselves from family and friends’ (M5). Some participants expressed a desire to reduce their own SMU to spend more time ‘meeting up with those people’ they were communicating with online (F5).

However, those who were more frequent users again indicated that online interactions generally replaced face-to-face out of necessity. Friends who were unable to socialise in person due to geographical constraints turned to social media to maintain peer-to-peer interaction. This applied to ‘long-distance friendships’ (F16), keeping in touch with friends at other schools, and those who did not live within walking distance to their close friends (F18).

Yes, that’s one of the reasons I use social media so much, it’s because all of my friends live so far away. I think my closest friend lives a 20-minute drive from me. So, I use social media to stay in contact with everyone, because that’s the only way you can really talk to people. (F19)

SMU was thus felt to strengthen or maintain peer connectedness for those with reduced opportunities for offline socialising, providing a protective effect from the risks of poor peer connectedness or loneliness.

SMU also promoted continuity of social networks, enabling young people to stay ‘connected’ (F12) with old friends from primary school, those who have moved away from the area, and friendships formed from extracurricular activities (F10). Without social media, there was a perceived risk that such ‘friendship[s] would just die’ (F16). Rather than ‘weak ties’ of vast online networks suggested by the displacement hypothesis [ 11 ], these were presented as close friendships whose enduring existence was stimulated by SMU in the absence of opportunities for offline interaction.

What social media is used for may influence whether it is perceived by the user to be displacing time spent with peers. Participant M1 pointed to the difference between playing PlayStation with a headset on, ‘talking to your friends… you are playing but also talking, so I feel more social, more talkative’ and ‘when you are using social media [passively], you feel isolated. You are just on your phone’ (M1). Whereas passive or excessive SMU may be perceived to displace face-to-face interaction, using social media explicitly for socialising may fulfil more of a stimulation function – enabling friends to ‘hang out’ (M4, M5) online when doing so in person is not possible.

In addition to maintaining stability within their social circle, SMU was also often credited with expansion of participants’ social circle through making new friends online, both by offering opportunities for new introductions, such as through a ‘mutual friend’ (F5), and by facilitating the development of friendships through initial online communication, which felt less intimidating than new face-to-face socialising (M4). Supporting the online enhanced self-disclosure or social compensation hypothesis [ 26 ] this was found to be particularly helpful to F6, who described herself as ‘shy’.

I feel like it’s easier for me because I feel like… if I’d just met someone, like, if someone just came to school now and we had to be friends, I feel like it would take me a while to, like, be able to talk to them without feeling… It depends. I think sometimes I’m really shy, and I think sometimes I’d rather just get to know someone online first… (F6)

As such, SMU was determined to be an important – and in some cases, critical – means of maintaining and expanding the size of young people’s social networks. SMU was explicitly credited by some participants for network expansion over and above friendship closeness. The network enhancing benefits they ascribed to SMU may be aligned to some extent with the ‘weak ties’ suggested by the displacement hypothesis, bringing limited psychosocial reward [ 11 , 13 ]. However, many young people in our sample referred to most of their online interactions and relationship maintenance being with existing close friends, illustrative of a stimulation effect. The importance of network size for well-being may vary across individuals, and a discussion between participants F6 and F7 noted the distinction between small numbers of ‘deep’ friendships (F6) that traverse online and offline worlds, and the tendency for some young people (including themselves at an earlier age) to place importance on having ‘loads of followers’ (F6) who were ‘fake friends’ (F7).

Social obligations

Whilst SMU enhanced feelings of connectedness through enabling participants to keep in touch with others, this was frequently accompanied by demanding expectations amongst peers. Participants reported feeling obliged – in line with social norms – to respond promptly to messages from peers and to provide positive feedback on peers’ social media posts. This was sometimes accompanied by feeling overwhelmed by multiple messages or group chats, guilt associated with making excuses for unavailability or outright peer conflict if expectations were not met. Rather than displacement or stimulation, we suggest this represents a situation of ‘over-stimulation’.

Obligation to be available

Most participants reflecting on their own active use of social media made implicit reference to a social media etiquette developed by their generation, to which they either adhered or chose to ignore. Participants felt they were expected to respond immediately to social media messages. Being available to take part in multiple online conversations simultaneously was felt to be ‘stressful’ and ‘a mess in my mind’ (M4), with ending conversations causing difficulty for several participants.

For me, it is actually hard, because I don’t have a way to end the conversation. I just go on another application and then after an hour or two, I check what they actually wrote and then they’re like, ‘Oh, you came back,’ and then I have to tell them a random explanation. I was like, ‘Oh, I went do something,’ or something, because I don’t want to tell them, ‘Oh, I couldn't be bothered to talk to you anymore,’ because that’s, kind of, a harsh way. (M4)

Participants often discussed their online communication in obligation-related terms as a means of avoiding conflict with peers, or as a chore necessary to adhere to social norms.

People don’t assume, “Oh, they're busy.” If my friend didn’t reply to me for a day, I’d instantly think, “Oh, have I done something wrong?” because I feel like a day is quite a long time to go without social media for us, so I’d just be like, “Oh, are they annoyed at me?” (F12)

This narrative of obligation or duty was underlined by terminology used by participants who reflected on the need to provide peers with an ‘excuse’ (F12, F15) to end online conversations or not to respond immediately to messages, with one participant ‘panicking’ (F14) when her phone was broken in case friends took offense to her lack of contact.

This aligns with neither the displacement nor stimulation hypothesis. These participants seemed to reveal a sense of ‘over-stimulation’ or ‘hyper-connectedness’ with peers, whereby perceived excessive or duty-bound online communication no longer enhanced friendship quality but became a burden attached to friendships.

Obligation to provide positive feedback

Several participants explained their motivation for commenting on a friend’s post as an act of altruism to boost others’ self-esteem, stimulating peer connectedness through provision of emotional support and mutual respect (F4, F5, F10). However, others conveyed a weight of expectation to do so to avoid negative consequences to the friendship. Failure to like or comment on pictures posted by friends was usually met with confusion (‘because it’s the normal thing to do’ (F11)), a need for justification, or conflict (M4).

While many participants accepted this etiquette as part of everyday peer relationships, others described it as time-consuming and ‘overwhelming’ (F15), with some feeling ‘forced’ (M4) to like or comment on a friend’s post. This emotive language seemed to convey a sense of excessive peer connectedness or over-stimulation emerging from unrealistic but increasingly normalised expectations of friendship.

Participant F12 described the process of commenting and liking on others’ posts as ‘trading’ to boost perceived popularity for enhanced peer status. This understanding that provision of positive feedback is expected rather than based on genuine positive evaluation of content may undermine the validating effect of receiving positive feedback oneself, leading some young people to view likes or comments received on their own content as a superficial form of popularity and undermining benefits to self-esteem.

In addition to extending the positive stimulation effect of online communication into negative feelings of oppressiveness, the concept of displacement is exemplified here through young people’s defining of friendship in the normative obligation to exchange likes and positive comments. These more potentially hollow popularity-based aspects of friendships are indicative of ‘weak’ ties – a superficial type of peer support compared to the deeper benefits of strong affective ties defined by close emotional, tangible support, mutual respect and trust [ 11 ]. However, peer popularity is a key aspect of identity development and sense of self in adolescence, and receipt of feedback to social media content may therefore still be an important contributor to well-being and peer connectedness for this age group [ 27 ].

The theme of (mis)trust encapsulated both positive and negative aspects of the role of SMU in social relationships. The dominant narrative presented social media as a vehicle through which participants’ parents could demonstrate their trust that they would behave safely and responsibly. This was generally reciprocated by participants, several whom trusted their parents or other family members to follow their social media accounts as a form of protection. One exception to this provided an example of a more complicated relationship with parents and felt a lack of trust to be left in charge of their own SMU, with implications for responding to adverse online experiences.

Where close friends were felt to be trustworthy, social media provided opportunities for self-disclosure, fostering intimacy in the relationship, and improving peer connectedness in a virtuous cycle. However, the fear of data misappropriation, such as screenshotting within broader peer networks, appeared to have led to widespread underlying feelings of mistrust, undermining peer connectedness. Rather than a linear effect of displacement or stimulation, displacement or undermining of social connectedness seemed to present in a poor-get-poorer effect, whereas good quality relationships were further stimulated by SMU in a rich-get-richer effect.

Opportunities for adults to demonstrate trust

With adolescents in control of their own online profiles and content, social media was felt by some to provide opportunities for adults in their lives to demonstrate they trust young people to be responsible online, nurturing their independence. Within the sample, there were positive examples of trusting parental relationships, in which parents had provided guidance and established boundaries, then let young people use social media without excessive interference (M1, F8, F10).

Several participants spoke of their parents or other family members following their social media accounts to keep an eye on them. This was generally framed positively as overseeing participants’ SMU for their protection, either in terms of giving advice about data privacy or inappropriate posts (F17), or in more practical terms, whereby geographical tags can help parents locate young people if they are unable to contact them (M4). Participant M4 also went on to discuss the barriers introduced by social media to prevent lying to his parents about his whereabouts. This was also framed positively as preventing potential damage to the relationship. The dominant narratives of mutual trust developing and being played out through parents’ navigation of young people’s SMU demonstrated the potential for stimulation of family connectedness.

However, one participant stood out in their portrayal of parents with strict attitudes to SMU, whereby access to certain apps or activities had been banned, describing a paternal relationship defined by restrictions and lies.

My mum gave [snapchat]to me when I was 10, and then my dad said I wasn’t allowed to have it. I kind of deleted it for a while, and then I discovered I could just hide it, so I had it on my phone. Then whenever he asked to use my phone, I’d delete it, and then download it again and put it back in when I got my phone back… (F1)

This participant also spoke of her parents looking over her shoulder as she used social media or taking her phone out of her hands to check what she was doing.

Those participants with parents who had demonstrated their trust reported feeling able to discuss and ask for advice on difficult issues encountered on social media, whereas those with less trusting parents felt reluctant to approach their parents for fear of repercussions. This is evident in contrasting comments from F14, who was comfortable approaching their mother for help with online peer relationships, and F1, who felt that her parents’ dogmatic approach to social media prevented her reporting online sexual harassment in case she was no longer allowed to use certain apps.

I mean she [mum] knows that you’re going to get follow requests from people you don’t necessarily know and she said, “You can accept them but just make sure you know what you’re getting into.” She’s like, “If anything gets too bad tell me because we’re not going to tell you off or anything. We want to understand and even if you’re in the wrong we’ll try to help you”. (F14)

But I wouldn’t tell my parents [about strangers’ sexual harassment online] because they wouldn’t let me have it any more, and I’m not really meant to have it anyway. (F1)

Participants who had established a sense of mutual trust with parents also noted an appreciation for constructive guidance and boundaries to SMU. This appeared particularly pertinent to night-time SMU and its potential to disrupt participants’ sleep patterns, where rules set by parents about SMU in bed were quickly found to be beneficial by participants F4 and F5. In this sense, an authoritative approach to setting sensible SMU boundaries – seemingly reflective of good family connectedness – seemed to be acceptable to young people. Family connectedness therefore has the potential to mitigate well-documented negative effects of night-time SMU on sleep [ 14 ].

Self-disclosure and fear of screenshotting (‘I don’t trust you’)

We found some evidence of online enhanced self-disclosure in our sample – in line with the stimulation hypothesis – whereby features of online communication facilitate sharing of intimate information, leading to better quality relationships [ 28 ]. Those participants who demonstrated online enhanced self-disclosure appeared to do so specifically because of perceived poor social skills. Participant F6 described herself as particularly lacking in social confidence and noted a preference for sharing sensitive disclosures via social media rather than at school where ‘everyone is always there’ (F6). In this case, the perceived privacy of direct messaging via social media with trusted close friends was felt to stimulate online self-disclosure and deepen the participant’s friendships. M1 also noted difficulties approaching friends face-to-face with a problem, but an ability to be ‘direct’ in doing so online. One participant gave a specific example of preferring online rather than face-to-face interaction in the case of a close bereavement, where giving condolences online would avoid an uncomfortable display of emotion (M4).

However, a more common perspective amongst our sample was a preference for face-to-face sharing when it came to sensitive or personal information. Reasons included the increased effort involved in typing long messages online (F5), ease of conversation and avoiding misunderstandings when able to gauge behavioural or vocal cues (F4, F7, F10, F11, F12, F14, F15, F18, F19), knowing who else is present and increased privacy offline (F2, M2, M3, M5, F8, F16, F17), and face-to-face as a less superficial and therefore more appropriate context for discussing serious problems (F9).

For many participants the risk of screenshots being taken and shared presented a substantial barrier to online self-disclosure (Fig.  1 ), with some saying they would not trust even close friends with sensitive information sent over social media. Others reserved any content sharing only for trusted close friends, and only using certain apps such as Snapchat where users are notified if someone has taken a screenshot. Fears included screenshots being used as ‘evidence’ (F13) or ‘proof’ (F15) within an argument, or to spread ‘rumours’ (F6), but also images being manipulated and used to ‘make fun’ of the subject (M3). Other participants blamed screenshotting for exacerbating peer conflict and for the potential ‘break[down]’ (M5) of friendships. For two participants (M2, M3), the risk of screenshotting and potential misappropriation of content put them off using any social media at all. In restricting online self-disclosure, this fear and mistrust of social media audiences represent a limit to online peer connectedness, aligned to the displacement of good quality face-to-face social interactions with less intimate ones online.

Implications of social media screenshotting for trust and poor peer connectedness

Concerns about deception and privacy issues appeared to be at the forefront of most participants’ minds as a result of their own or peers’ experiences, or anxieties raised by parents. These worries ranged from trusting (or not) their friends to sensitively handle content shared privately, feeling ‘suspicious’ (F8) when contacted by strangers as to their identity and intentions, to a general undercurrent of mistrust of social media audiences not to ‘hack’ (M4) their accounts, ‘steal’ (F18, F19) their data or identity or engage in other ‘scary’ (F2) behaviour.

Probably if I had to think of something off the top of mind, I would probably say the most important thing on social media is, don’t talk to someone you don’t know, because you don’t know what they’re capable of. (M4)

The young people in our sample were thus acutely aware of the risks of identity theft and of engaging online with potentially dangerous strangers. Combined with a general discomfort with online self-disclosure or fear of screenshotting among peers, this mistrust can simultaneously be perceived as a challenge to quality in peer relationships and interpreted as a constructive strategy for mitigating risk.

Personal and group identity

Social identity development and expression can be facilitated through SMU. Using social media to share experiences – messaging, viewing online content together with friends and family, and co-producing content such as TikTok videos – appeared to foster feelings of connectedness through stimulation of a sense of belonging. Participants described careful curation of their online profiles to construct and express their identity. Online social networking and microblogging enabled those with specific interests (such as art or music) or experiences (including mental health conditions) to find like-minded others and join communities without geographical constraints, thus enhancing peer connectedness.

In terms of family connectedness, frustrations with adults’ lack of understanding of young people’s SMU and overemphasis on online harms led to a perceived disconnect between generations. Rather than displacement weakening family connectedness here, an adult discourse of SMU displacing activities they perceived to be healthier had negative implications for highlighting differences between generational groups and reducing feelings of mutual respect and understanding.

Sense of belonging

SMU stimulated feelings of social connectedness via enhancing feelings of belonging and group membership. For some participants, this was achieved simply through inclusion in a group chat (F3, M4).

In other cases, appearing on Instagram stories, ‘slip stories’, or private stories of their friends – whether as actors within the content or as privileged audiences of this restricted content – helped to cement participants’ position as a trusted member of the peer group (M4) and was generally perceived to symbolise a close friendship (F1, F2, M4, F9, F11). In such cases, privacy settings became markers of group membership.

In line with the stimulation hypothesis, SMU enabled and made salient shared experiences with existing friends and family, an important part of social group membership. Several participants highlighted the shared enjoyment of passively consuming social media content in the presence of others. This included watching YouTube videos together with family members (M3), sharing funny memes with parents (M1, F8), and using content related to special shared interests (such as football) to enrich interactions with siblings and improve the closeness of the relationship (F6). In addition, active co-production of visual content with others was presented as an important part of friendship for some (F9) and a way to ‘make memories’ with friends (F5). This co-production could improve peer connectedness through collaboratively working to achieve a common creative goal and sharing in a sense of accomplishment.

For some participants (F18, F19, F2), social media represented an opportunity to express their opinions and share creative projects with like-minded others outside their immediate friendship groups, with whom they would otherwise be unlikely to interact because of differences in age or location. Using social media in this way gave them access to communities in which they could receive support in shaping their artistic identities as well as becoming active and supportive community members. Identity development and expression was thus supported by SMU, simultaneously stimulating connectedness to a wider peer network.

Generational disconnect

Many participants expressed a sense of frustration with what they perceived to be an adult obsession with screen-time and the negative effects of SMU, which seemed to impact negatively on family identity and connectedness. Growing up in a vastly different environment to their elders – largely but not exclusively related to the advent of social media – was felt to have led to a disconnect between generations, whereby adults were perceived as unable ‘to relate’ (F10, F14, F15). As such, there was a sense that adults fail to fully appreciate the significance of the online world for this generation, imposing arbitrary screen-time limitations rather than taking time to understand the positive and negative aspects of SMU.

Older generations were felt to overestimate the negative impacts of SMU (‘adults think it’s bad but it’s not that bad…’ (F13)) with too much importance placed on social media as a cause of bullying or harm, when the relationship as experienced by young people, is more complex.

I think the biggest problem with social media is adults say, “It’s evil, you shouldn’t do it,” but the thing is- and they’re like, “It creates argument, you bully each other.” It doesn’t. The thing is the arguments are going to happen anyway, it just doesn’t help you resolving it really. People are like, “Oh it creates arguments. It turns people into bullies. You’re vulnerable on there.” It isn’t really. That’s the thing. (F13)

Several participants relayed experiences whereby their parents or other family members had been critical of their SMU, with a general negative ‘stigma’ attached to social media (F10). While this was sometimes perceived as a justifiable concern around online harms (F4, M4), those who were told to simply ‘get off your phone’ (F12) felt misunderstood and some found this irritating or upsetting (F2, F10, F11, F12, F14, F15). Participant F14 described her mother’s dismissive attitude towards social media. Her mother suggested that her SMU displaced time better spent on healthier activities such as exercise and face-to-face socialising, but was felt to underestimate the social importance of SMU and the diverging priorities between generations. With social media often used strategically at times when such activities are logistically more difficult (as discussed under ‘displacement of face-to-face socialising’), this perceived inappropriate emphasis on displacement and screen-time restrictions appeared to underlie the sense of disconnect between young people and older generations. These age-related group differences – accentuated by divergent attitudes to SMU – have the potential to increase inter-generational discord, harming family connectedness through diminished feelings of mutual understanding and respect.

This qualitative study contributes to a growing literature on the psychosocial impacts of SMU in adolescence. We explored in depth the role of SMU in the broader social environment from the perspectives of adolescents themselves, examining both peer and family connectedness. Four themes were identified: i) ‘Displacement of face-to-face socialising’ (ii) ‘Social obligations’ (iii) ‘(Mis)Trust’ and (iv) ‘Personal and group identity’.

Findings in relation to displacement and stimulation hypotheses

We found some limited evidence in favour of the displacement hypothesis [ 11 ], whereby time spent using social media was felt by some participants to displace time spent socialising with family or friends face-to-face. However, it was often the case that online peer interactions took place mainly when in person socialising was not possible, providing opportunities to socialise and maintain peer relationships online in the absence of offline opportunities. Those experiencing increased SMU in place of family socialising tended to relay lower levels of family connectedness that preceded the SMU, with SMU used strategically to overcome feelings of loneliness in the home. This supports a ‘poor-get-poorer’ or ‘social deterioration’ effect, whereby those who feel less connected to their family are likely to rely more on SMU for social interactions or to alleviate boredom at home, further compounding a lack of connectedness within the household. Considering peer and family connectedness together, this is also illustrative of a ‘poor-get-richer’ or ‘social compensation’ effect, whereby poor family connectedness leads to increased online socialising with friends and subsequent improved peer connectedness. SMU may therefore serve as a protective tool in some circumstances to mitigate psychological risks associated with poor family connectedness or reduced face-to-face socialising. It is worth noting that these interviews took place before the COVID-19 pandemic led to school closures and lockdown, and SMU is likely to have served a particularly important function in this regard over the course of the pandemic.

One of few studies examining SMU and family connectedness, a cross-sectional survey of Canadian adolescents [ 29 ] found that heavy SMU (3 or more hours per day) was associated with greater odds of negative reported relationships between mothers and daughters, fathers and daughters and fathers and sons, but not mothers and sons. The authors explain their results as indicative of SMU displacing time spent engaging face-to-face with parents, with negative consequences for family relationships, However, our findings indicate that adolescents may also be motivated to turn to social media as a result of existing poor family connectedness.

Our study provides more evidence for the stimulation hypothesis, whereby SMU enhances the user’s existing social resources through increased contact and maintenance of relationships. Perceived benefits of SMU that emerged in this sample included the expansion of social networks, the ability to keep in touch with friends and family (including those for whom geographical constraints prevent offline socialising), enhanced self-disclosure for socially awkward young people or among very close friends, and supporting identity development and feelings of belonging. Consistent with a ‘poor-get-richer’ effect, those with reduced social resources offline – not only due to social awkwardness or anxiety but also loneliness or geographical barriers to offline interaction – find online support particularly beneficial [ 17 ,  27 ].

Where close friends were felt to be trustworthy, social media provided opportunities for self-disclosure, fostering intimacy in the relationship and improving peer connectedness in a ‘rich-get-richer’ or ‘social enhancement’ effect (Fig.  2 ). This is in line with previous research finding that adolescents’ time spent on instant messaging services enhances time spent face-to-face with friends, and subsequent quality of friendships [ 20 ]. SMU also provides opportunities for young people to construct, express, and develop identity in relation to their social world [ 30 ]. Young people in our sample reported using social media to share experiences, such as passively watching entertaining content together with friends and family members, as well as actively co-producing content, with privacy settings used to demarcate friendship group boundaries to different degrees of closeness (Fig. ​ (Fig.2). 2 ). This may foster feelings of connectedness and belonging, in line with the stimulation hypothesis.

Social enhancement (rich-get-richer) effect of social media in connectedness within close friendships

In addition to the positive aspects of SMU, young people reported feeling pressures of expectation around providing feedback on friends’ online posts and being constantly available for communication. For these young people, social media had created a normative environment of ‘over-stimulation’, which fostered feelings of stress. It may be that SMU for direct peer communication may stimulate connectedness and subsequent well-being to a point, whereas excessive communication and the associated expectations to respond might undermine these benefits. This aligns to the 'digital Goldilocks hypothesis' [ 24 ] and other evidence of a curvilinear relationship between SMU and psychosocial adjustment [ 23 ], whereby moderate SMU is beneficial to well-being (compared to no use at all) but excessive use is associated with negative outcomes. In addition, the fear of data misappropriation such as screenshotting within broader peer networks appeared to have led to widespread underlying feelings of mistrust, thus undermining peer connectedness, and lending weight to the suggestion that broader SMU may discourage development of ‘strong ties’. Screenshotting is a currently understudied aspect of SMU. Our findings suggest the role of screenshotting within relationships between SMU and psychosocial outcomes – including social connectedness – warrants further attention.

Parental understanding of social media use in young people

Where a family environment of mutual respect had been established and consideration had been given to understanding the indispensable role of social media in young people’s lives, with positive aspects acknowledged in addition to traditional e-safety concerns, young people were more accepting of advice and clear boundaries regarding healthy SMU. Young people felt they were trusted to behave responsibly online and in turn trusted authority figures to provide guidance regarding challenges encountered without fear of access to social media being removed or restricted. Risks to peer connectedness encountered online, such as cyber-ostracism or screenshotting, may thus be mitigated by strong family connectedness. With this supportive environment, young people are able to navigate online difficulties but also feel encouraged to share positive social media content with family members, promoting shared interests and family identity. A ‘rich-get-richer’ [ 19 ] effect appears to develop, with social media promoting further trust and family connectedness (Fig.  3 ).

Social enhancement (rich-get-richer) effect of social media in family connectedness

Conversely, an existing lack of trust in relationships between young people and their parents may underpin a rejection of screen-time restrictions and a reluctance to report exposure to online harms, adding further to a sense of social distance and further undermining connectedness, consistent with a ‘poor-get-poorer’ effect (Fig.  4 ). Future research might explore whether these findings can be generalised to the wider population of young people, and test the relationship between parental attitudes to social media and young people’s resilience or vulnerability to online harm.

Social deterioration (poor-get-poorer) effect of social media in family connectedness

Limitations

This study has some important limitations. Our sample size was somewhat smaller than planned due to the emergence of COVID-19, with boys in particular under-represented. However, a broad range of views and experiences were captured in the sample, which were sufficient to enable rich themes to be generated [ 31 ]. While our sample was diverse in their experiences of social media, they were not selected on the basis of how much they used SMU or for what reasons, therefore it is possible that some additional patterns of SMU may exist in this age group that were not captured. All participants were aged 13–14-years and attended inner-city secondary schools in one area of the country. Different offline experiences and circumstances are likely to be accompanied by different online experiences, and caution should therefore be exercised in generalising findings from this study to other populations.

Implications

The separation of the social environment offline and on social media is not clear cut. Focusing on developing trusting, attentive relationships with peers and parents offline is likely to optimise the potential for social media to further benefit social connectedness. Feeling understood and respected by adults should encourage young people to accept and appreciate healthy boundaries established regarding their digital activities. A balance must be sought between teaching young people about the risks to well-being that engaging with social media may lead to, without being alarmist and creating a culture in which confidence in others is discouraged. Healthy peer relationships in which there is trust, respect, and space to ignore digital notifications and messages are likely to benefit most from SMU that enables enhanced self-disclosure and increased closeness without feeling oppressive. Young people should be supported to re-prioritise trustworthiness over availability in defining meaningful and fulfilling friendships. If, as our evidence suggests, the online social environment is an extension of relationships in the real world, fostering healthy connectedness with others offline is likely to maximise the social benefits and minimise the potential harms of social media for young people.

Conclusions

Rather than a clear, unidirectional relationship in which SMU harms – through a process of displacement – or enhances – through stimulation – overall social connectedness in adolescence, we suggest a complex set of reciprocal and circular relationships in which social media can play both a beneficial role in reinforcing existing positive connections to peers and family, and a deleterious role in exacerbating an already poor social environment through the propagation of mistrust. The relationship between SMU and social connectedness cannot be viewed as independent of either content or context. In addition to quality of existing offline social resources, the different activities and ways in which adolescents use social media will partially determine the direction and valence of effects. Passive SMU, devoid of social interaction, is unlikely to confer the same social benefits as SMU for direct communication with friends. However, parents and other adults supporting young people should also take account of individual differences in how social media may benefit or undermine connectedness, supporting individuals to find ways to interact with social media that best supports their well-being.

Acknowledgements

We are extremely grateful to the young people who spoke to us about their experiences of adolescence in the age of social media, and to the teaching staff who took time to organise the interviews.

Abbreviation

Authors’ contributions

LW coordinated the study, carried out the interviews and drafted the manuscript; All authors conceived of the study, and participated in its design and in interpretation of the data. BM, CMAH, and JK critiqued the output for important intellectual content. All authors read and approved the final manuscript.

This study is funded by the National Institute for Health Research (NIHR) School for Public Health Research (SPHR) (Grant Reference Number PD-SPH-2015). CMAH is supported by a Philip Leverhulme Prize. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funders had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Availability of data and materials

Declarations.

The study was approved by and carried out in accordance with the University of Bristol Faculty of Health Sciences Ethics Committee (Ref: 84883). Informed consent was obtained by parents or legal guardians of participants involved in the study as well as participants themselves.

Not applicable.

We have no known competing interests to declare.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Adolescence

More research questions the “social media hypothesis” of mental health, a new study shows that social media does not lead to anxiety or depression..

Posted August 10, 2023 | Reviewed by Gary Drevitch

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• A new study found that when teenagers used social media more, their mental health did not change over time.
• Mainstream media should devote more coverage to studies like this one.

As I’ve discussed previously , conventional wisdom suggests that using social media promotes poor mental health, especially in teenagers . But there is good reason to question this idea. As more high-quality research becomes available, we can see room for nuance and see that social media is not consistently detrimental to everyone’s well-being.

A critical limitation in many existing studies on this topic is that they are cross-sectional. This means all variables are assessed only once, and at the same time. This isn’t necessarily a bad thing; it just means we don’t know how behavioral changes over time might be associated with changes in emotional variables. Longitudinal research helps us to better understand how change happens by measuring these variables repeatedly over a period of months or even years.

Longitudinal research is especially valuable in this case because some young people may use social media to alleviate distress , so we might observe that increases in depression or anxiety will predict increases in social media use , rather than the reverse. On the other hand, if the social media hypothesis is correct, then as teenagers spend more and more time online, this should be followed by decreased mental health (i.e., greater anxiety/depression). But that’s not what the data reveal.

What Researchers Found

A research team in Norway recently published a study in which they tracked young people aged 10-16, and assessed them every 2 years. Each time, the researchers interviewed participants about their behaviors online (e.g., posting photos, “liking,” or commenting on others' posts), and they conducted clinical assessments of depression and anxiety with standardized psychiatric measures. The researchers found no evidence that increased social media use was followed by elevated anxiety or depression. This means that as these teenagers used more social media, their mental health did not change. These findings directly contradict the idea that social media use leads to poor psychological well-being.

The authors are careful to note that even though social media did not make teenagers feel worse, on average, it also did not make them feel better. So, social media use may not have an overall negative or positive effect for the average teenager. This idea is consistent with what I have argued previously , which is that social media use may have differential effects depending on the user’s initial motivations. When people are motivated to use social media because they find it interesting or rewarding, then it’s likelier to make them happy, whereas when they feel compelled or obligated to use it, then it’s likelier to make them feel worse. Motivations matter more than the technology itself.

The researchers also suggest that perhaps subgroups of teenagers may experience different outcomes following social media use, such as those who are bullied or have low self-esteem . The specific content that people view on social media may also play a role. It is also true that digital technologies change rapidly and we cannot assume that all future forms of social media will operate the same way psychologically. New applications have the potential to be better or worse than what people currently use.

Time Trend Data Are Inconclusive

Those who hold with the “social media hypothesis” of mental health will often point to time trend data as evidence. They argue that because social media use has risen in teenagers over the past 15 years, and that teen depression and anxiety has also risen over the same period of time, then those two trends are likely connected.

But if that were true, we ought to be able to observe this trend happening during teenagers’ lives. The fact is, we do not observe this pattern, and these null findings should make us skeptical about such claims. When researchers track teenagers’ mental health over a span of years, there is no link between their social media use and their experiences of depression or anxiety. In the words of the authors , “ the frequency with which adolescents engage in behaviors like posting, liking, and commenting on others’ posts does not influence their risk for symptoms of depression and anxiety .”

It would be great to see more mainstream media coverage of studies like this, especially considering the widespread belief that if young people are permitted to use social media, their mental health will deteriorate. Perhaps parents of teenagers can take some comfort in the fact that for the average user, there is little risk of this.

Cauberghe, V., Van Wesenbeeck, I., De Jans, S., Hudders, L., & Ponnet, K. (2021). How Adolescents Use Social Media to Cope with Feelings of Loneliness and Anxiety During COVID-19 Lockdown. Cyberpsychology, behavior and social networking , 24 (4), 250–257. https://doi.org/10.1089/cyber.2020.0478

Puukko, K., Hietajärvi, L., Maksniemi, E., Alho, K., & Salmela-Aro, K. (2020). Social Media Use and Depressive Symptoms—A Longitudinal Study from Early to Late Adolescence. International Journal of Environmental Research and Public Health , 17 (16), 5921. MDPI AG. Retrieved from http://dx.doi.org/10.3390/ijerph17165921

Steinsbekk, S., Nesi, J., & Wichstrøm, L. (2023). Social media behaviors and symptoms of anxiety and depression. A four-wave cohort study from age 10–16 years. Computers in Human Behavior , 147 , 107859.

Dylan Selterman, Ph.D., is an Associate Teaching Professor at Johns Hopkins University in the Department of Psychological and Brain Sciences. He teaches courses and conducts research on personality traits, happiness, relationships, morality/ethics, game theory, political psychology, and more.

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Cultivation Theory In Media

Ayesh Perera

B.A, MTS, Harvard University

Ayesh Perera, a Harvard graduate, has worked as a researcher in psychology and neuroscience under Dr. Kevin Majeres at Harvard Medical School.

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Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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On This Page:

Key Takeaways

• George Gerbner introduced cultivation theory in the 1960s as part of the Cultural Indicators Project to examine the influence of television on viewers.
• Cultivation theory holds that long-term exposure to media shapes how media consumers perceive the world and conduct themselves.
• The cultivation hypothesis states that the more television people watch, the more likely they are to hold a view of reality closer to television’s depiction.
• For many individuals, the distorted and partial reality portrayed on television represents what the world is “really” like.
• Gerbner also coined the term mean world syndrome to describe the cognitive bias whereby television viewers exposed to violent content were more likely to see the world as more dangerous than it actually is.
• In more recent times, researchers have delved into other forms of media, such as reality TV and video games, to study the effects of cultivation theory.

What is Cultivation Theory?

Cultivation theory is a communications and sociological framework which posits that long-term exposure to media shapes how the consumers of media perceive the world as well as conduct themselves in life (Nabi & Riddle, 2008)

Cultivation theory (or cultivation analysis) was introduced in the 1960s by Hungarian-born American professor George Gerbner to examine television’s influence on viewers (Gerbner, 1969). The findings of Gerbner were later expanded upon and developed by the American screenwriter Larry Gross.

This theory implies that those exposed to media interpret social realities according to how such realities are portrayed in the media.

Television’s ability to stabilize and homogenize societal views is an example of cultivation theory. Children who watch commercial TV have notably more sex-stereotypical views of women and men than children who don’t watch commercial TV.

Of particular interest during the initial stage of research was the possible impact of exposure to violence on the viewers of television programs (Settle, 2018).

Gerbner’s introduction of cultivation theory was part of the larger Cultural Indicators Project which was a research study commissioned for the National Violence Commission (Gerbner, Gross, Morgan & Signorielli, 1986).

In addition to cultivation analysis, which examined how the media shaped its consumers’ perception of reality, the Cultural Indicators Project also analyzed two other related spheres (Vinney, 2020).

It engaged in institutional process analysis, which examined the formulation and the distribution of media messages, and message system analysis which explored the aggregate content of media messages.

Cultivation Theory and Television

Gerbner’s primary focus was centered on the role of television. This approach also involved several key assumptions. First, television was distinguished as a unique form of mass media (Gerbner et al., 1978).

For instance, it was simultaneously auditory and visual but did not require literacy. Furthermore, access to television was almost universal. Additionally, the engaging narrative style that television programming generally employs could readily capture the viewers’ attention.

The second assumption held that television influences society’s manner of relating and thinking (Settle, 2018). Both Gerbner and Gross, for instance, held that the consciousness cultivated by television involved the standards of judgment as well as the facts of life (Gerbner & Gross, 1972).

Gerbner further observed that television stabilized societal patterns and induced resistance to change (Gerbner, Gross, Jackson-Beeck, Jeffries-Fox & Signorielli, 1978).

Thirdly, Gerbner’s approach held that the effects of television were limited (Gerbner et al., 1978).

Television, herein, was identified as part of a larger sociocultural system. Therefore, the aggregation of its effects in a certain direction was considered substantially more critical than the singular effect of a certain program at a particular point in time (Gerbner, Gross, Morgan & Signorielli, 1980).

Gerbner, hence, pointed out that while watching television per se might not cause a certain behavior, watching television over time could significantly influence how we perceive the world (West & Turner, 2014).

The Mean World Syndrome

During the exploration of the effects of television viewing, Gerbner (1980) also coined the term mean world syndrome to describe the cognitive bias whereby television viewers exposed especially to violent content were more likely to see the world as more dangerous than it actually is.

Because television programming significantly shaped attitudes toward and opinions of reality, regular viewers of violent content were likely to experience more fear, pessimism, increased anxiety, and greater alertness to imaginary threats.

Alternatively, those who watched little television were more likely to view the world as less dangerous (Vinney, 2020).

Mainstreaming and Resonance

As cultivation theory gained more traction, Gerbner and his colleagues introduced the concepts of mainstreaming and resonance to further refine their theory.

Mainstreaming

Mainstreaming is the process wherein consistent exposure to the same labels and images induces television viewers from diverse backgrounds to adopt a homogenous outlook of the world (Griffin, 2012; Perse, 2005).

Therefore, traditional distinctions among groups are blurred by the emergence of a new worldview that shifts the mainstream to the interests of the sponsors of television.

Consequently, heavy television viewing can potentially override individual perspectives in favor of a melting pot of cultural and social trends (Gerbner, Gross, Morgan & Signorielli, 1994).

Resonance is the similarity that television narratives may share with the everyday lives of the viewers (Gerbner, 1998).

According to Gerbner, this congruence constitutes a double dose of messages which amplify the effects of cultivation. Such amplified patterns of cultivation may significantly impact society (Griffin, 2012).

For instance, when those who have already experienced crimes see more violence on television, their perception of the world as scary is further enhanced.

This reinforcement of belief can lead them to demand more security and safety measures from governmental authorities.

Building upon the foundation of Gerbner, scholars, more recently, have ventured into other spheres to study the effects of cultivation theory.

For instance, while Gerbner was primarily focused on fictional television, these researchers have delved into other forms of media, such as reality TV and video games.

They have also explored the effects of phenomena other than violence.

For example, Dmitri Williams (2006) conducted research to ascertain whether, from the standpoint of cultivation theory, video games wield the same influence television has in shaping social reality perceptions.

In this field study, wherein the subjects were to play an MMORPG game, a strong correlation indicating the impact of cultivation was found.

Moreover, a research study involving music videos, wherein the musicians endorse alcohol, revealed that exposure to such music videos could create an unrealistic view of alcohol consumption (Beullens, Roe & den Bulck, 2012).

Additionally, research into the communication of hip-hop journalism to impressionable audiences revealed that adolescent fans of hip-hop celebrities were more likely to engage in violence when such celebrities recommended violent conduct (Oredein, Evans & Lewis, 2020).

Furthermore, a research study examining social media’s impact on immigrant cultural adaptation suggests that immigrants using mainstream social media while adapting to a host culture would perceive their new environment based on the messages of such media (Croucher, 2011).

The study also implies that this cultivation effect would impact even the offline interactions between these immigrants and their host country’s natives.

A number of scholars have critiqued Gerbner’s description of cultivation theory. Some of these criticisms focus on the theoretical flaws of cultivation theory.

For instance, one argument posits that cultivation theory employs methods of the social sciences to address questions pertaining to the humanities (West & Turner, 2010).

Another argument asserts that the apparent relationship between television and the fear of violence might be misleading especially given the possibility that a third factor might be causing both phenomena (Griffin, 2012).

A third related argument questions the theory’s utility due to its ignoring of cognitive processes like rational thinking (Berger, 2005).

Additionally, it is possible that individuals’ lived experiences are more responsible for their perception of the world than is the cultivation effect.

For instance, Daniel Chandler points out that those living in high-crime regions are more likely (than those in safer areas) to stay home, watch television and become convinced that they are more likely to be victims of crime (Chandler, 2011).

Chandler reasons that this direct experience of the viewers would decrease the cultivation effect.

Chandler also notes that cultivation theory is misleading in its assumption of homogeneity in television programs (Chandler, 2011).

Horace Newcomb further adds that television could not cultivate the same perceived reality for every viewer because its presentation of violence is not uniform (Newcomb, 1978).

Moreover, Shanahan and Morgan argue that television viewers do not exclusively watch isolated genres, and consequently, the influence of a particular program type should be evaluated in the context of the aggregate viewing experience of the television watchers (Morgan & Shanahan, 2010).

In response to some criticism, attempts have been made to combine heuristic processes with cultivation theory to evaluate how the vividness of the violence on television influences the cultivation effects (Riddle, 2010).

Frequently Asked Questions

What is the cultivation analysis.

Cultivation analysis (or cultivation theory) is a social theory that proposes that long-term exposure to television and media gradually “cultivates” viewers’ perceptions of reality.

Developed by George Gerbner, the theory suggests that the more time people spend watching television, the more likely they are to perceive the real world in ways that align with the most common and recurring messages and representations depicted on television, often leading to a misperception of reality.

What is cultivation theory in social media?

Cultivation theory in social media suggests that prolonged engagement with social media platforms can shape users’ perceptions of reality, similar to the effects of long-term television viewing.

Users’ views on societal norms, values, and expectations may be influenced by the most recurrent themes and portrayals on social media, potentially leading to distorted perceptions of reality or an altered sense of social norms and behaviors.

When you see something on tv, and you assume that it must be true, you have experienced what aspect of cultivation theory?

If you see something on TV and assume it to be true, you have experienced what is known as the “mainstreaming” aspect of cultivation theory.

Mainstreaming suggests that persistent exposure to televised media leads to a homogenization of perceptions, where viewers’ beliefs and values align with the most common and repetitive messages seen on TV, regardless of their real-world validity or accuracy.

Berger, C. R. (2005). Slippery slopes to apprehension: Rationality and graphical depictions of increasingly threatening trends . Communication Research, 32 (1), 3-28.

Beullens, K., Roe, K., & Van den Bulck, J. (2012). Music video viewing as a marker of driving after the consumption of alcohol. Substance Use & Misuse, 47 (2), 155-165.

Croucher, S. M. (2011). Social networking and cultural adaptation: A theoretical model. Journal of International and Intercultural Communication, 4 (4), 259-264.

Gerbner, G. (1998). Cultivation analysis: An overview . Mass Communication and Society, 1 (3-4), 175-194.

Gerbner, G. (1969). Toward “cultural indicators”: The analysis of mass mediated public message systems . AV Communication Review, 17 (2), 137-148.

Gerbner, G. & Gross, L. (1972). “Living with television: The violence profile”. Journal of Communication. 26 (2): 173–199.x

Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1980). The “mainstreaming” of America: violence profile number 11 . Journal of Communication, 30 (3), 10-29.

Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1986). Living with television: The dynamics of the cultivation process . Perspectives on Media Effects, 17-40.

Griffin, E. (2012). Communication Communication Communication . New York: McGraw-Hill.

Gerbner, G., & Morgan, M. (2010). The Mean World Syndrome: Media Violence & the Cultivation of Fear . Media Education Foundation documentary transcript [http://www. mediaed. org/transcripts/Mean-World-Syndrome-Transcript. pdf, 19, 2020.

Morgan, M., & Gerbner, G. (2002). Against the mainstream: The selected works of George Gerbner . P. Lang.

Morgan, M., & Shanahan, J. (2010). The state of cultivation . Journal of Broadcasting & Electronic Media, 54 (2), 337-355.

Newcomb, H. (1978). Assessing the violence profile studies of Gerbner and Gross: A humanistic critique and suggestion. Communication Research, 5 (3), 264-282.

Oredein, T., Evans, K., & Lewis, M. J. (2020). Violent trends in hip-hop entertainment journalism. Journal of Black studies, 51 (3), 228-250.

Riddle, K. (2010). Always on my mind: Exploring how frequent, recent, and vivid television portrayals are used in the formation of social reality judgments. Media Psychology, 13 (2), 155-179.

Settle, Q. (2018). Introducing Communication Theory: Analysis and Application. Journal of Applied Communications, 102 (3), 1d-1d.

West, R. & Turner, L. H. (2010). Introducing Communication Theory: Analysis and Application (Fourth ed.). New York, NY: McGraw-Hill.

West, Richard; Turner, Lynn (2014). Introducing Communication Theory: Analysis and Application . New York, NY: McGraw-Hill Education. pp. 420–436.

Williams, D. (2006). Virtual cultivation: Online worlds, offline perceptions. Journal of Communication, 56 (1), 69-87.

Further Information

Cultivation Analysis: an Overview

Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1986). Living with television: The dynamics of the cultivation process. Perspectives on Media Effects, 17-40.

A Guide How to Create Social Media Case Studies that Convert (with Template)

Do you really need another piece of content to move leads through your sales pipeline?

With so much noise on social media platforms, many marketers might wonder if case studies are still relevant. The answer is yes, but only if they’re done right.

According to a 2024 survey from Statista , social media and video-sharing platforms are now the leading digital touchpoints for U.S. consumers, with 44% citing them as their primary interaction points. Ignoring these platforms means missing out on key opportunities to increase brand awareness and connect with potential customers.

Crafting a compelling social media marketing case study remains one of the best strategies for engaging future customers or digital agency clients.

But it’s not as simple as throwing together some numbers and calling it a day.

In this article, we’ll break down what makes a case study truly convert and how to strategically share it across social media channels. Plus, we’ll provide a template to help you get started.

Let’s jump in.

The importance of social media case studies in social media campaigns

There’s a lot of content out there.

Your potential customers are constantly bombarded with whitepapers, e-books, 10-step guides, newsletters and unpalatable sales hype. To get the attention of prospects today you have to demonstrate your product or service’s value, not just talk about it. 

B2B buyers today don’t have time to interpret marketing messages that aren’t concise and relevant. That means that instead of aimlessly beating around the bush about how great your company is and how terrific your products are, you have to share the real-life experiences customers are having with you and your products.

Traditional marketing tactics don’t work anymore. We already know that. People nowadays drive their own buying decisions through online research, and the importance of social proof cannot be understated. 

About 57% of the customers will only use or buy a business service if it has at least 4 or five-star ratings. It should be noted, however, that reviews aren’t enough. In fact,  88% of consumers view ratings and reviews as a personal suggestion, not definitive proof of a product’s efficacy. 

Reviews are all good, but creating in-depth, data-driven case studies is the way to go if you’re marketing B2B software or digital marketing agency services. Case studies are extremely effective in the consideration stage of the buyer’s journey when they actively compare solutions and providers to solve a problem they’re experiencing.

Examples are many, such as:

• Digital marketing agency : A digital marketing agency can use a social media case study to showcase how they helped a small business refine its social strategy and achieve specific campaign goals. The case study can highlight key metrics and impressive results like engagement rates, website traffic, and new clients acquired. It provides prospects with clear evidence of the agency’s ability to deliver results and helping them evaluate their options when comparing service providers.
• Influencer marketing consultancy : An influencer marketing consultancy can create a case study demonstrating how they connected brands with influencers who resonated deeply with the target audience. The study can emphasize the types of content created, the campaign’s success in driving engagement, and how it generated buzz around the brand..
• B2B software provider : A B2B software provider can present a case study illustrating how their solution helped a client streamline content creation efforts, leading to significant efficiency improvements and a noticeable rise in website traffic. Such a real-world success story provides valuable social proof during the consideration stage.
• Social media management platform : A social media management platform can share a case study that outlines how a brand utilized the platform to create and manage social media content across multiple channels. The case study could highlight the resulting improvements in engagement rates and alignment with campaign goals – all to help prospects see how the platform stacks up against competitors in the market.
• Creative agency : A creative agency can use a case study to demonstrate how they developed a successful new campaign for a brand, tapping into the latest trends and content formats to capture audience interest. Such a study can focus on the measurable impact, such as increased brand visibility and the acquisition of new clients.

As we already mentioned, your prospects are actively researching your products, and there’s quite a chance that they will stumble upon content from your competitors. Relevant resources like case studies can cement your brand as an authority figure. 

Now that you know why case studies are important, it’s time to tackle the creation process. 

The ingredients for a perfect case study 

1. detailed and data-driven info.

A great case study isn’t just a vague story of success – it’s built on concrete data. For example, instead of stating that a client “doubled traffic,” clarify what that actually means. Did visits jump from 50 to 100, or from 5,000 to 10,000? This level of specificity makes the impact of your work clear to prospective clients.

Highlight the exact ways your product or service made a difference. Include key metrics like a decrease in ad spend, an increase in organic followers, or improvements in engagement rates. Data like this gives your case study weight, especially for digital agencies where results speak louder than promises.

Remember, not everyone is an analytics expert. Break down complex data into digestible pieces so that anyone can understand the value of your work. Contextualize the numbers within the broader narrative to ensure they enhance your story rather than overwhelm the reader.

Checklist :

• Include specific metrics that clearly show the impact of your work.
• Simplify analytics and KPIs for a broad audience.
• Support data with visuals like graphs, real-time dashboards, or screenshots.

2. A compelling and complete story of a social media campaign

Storytelling allows your audience to connect emotionally and intellectually with your client’s journey. Begin with the customer’s challenges, walk through your solution’s impact, and finish with the results. This structure makes the story easy to follow and impactful.

When crafting your subject’s persona, focus on answering key questions: Who is the customer? What do they do? What were their goals and needs? The answers help paint a vivid picture that readers can relate to. Structure your narrative by splitting the main points into three clear sections: the challenge, the impact you had, and the final outcome.

A great story isn’t just about the hard facts—it’s also about the emotional benefits. Did your solution improve workplace morale, free up time, or reduce stress? Use quotes from the client to make the case study more personal and relatable. Additionally, include insights from your own team. Potential clients will appreciate learning how your team overcame specific challenges and delivered results.

• Structure the story with a clear beginning (challenge), middle (impact), and end (outcome).
• Include emotional benefits alongside data-driven results.
• Use quotes from both the client and your team to add a personal touch.

3. Relevant and engaging visuals

Visuals transform raw data into a more engaging experience. Each case study needs them! However, simply adding screenshots or images isn’t enough. The visuals need to be purposeful and align with your story.

Start with a catchy headline that clearly indicates what the case study is about. Then, arrange your visuals thoughtfully. Avoid cluttering the page. Leave plenty of negative space to keep the layout clean and easy on the eyes. Visuals should enhance the reader’s understanding of the data, not overwhelm them.

When gathering creative assets, focus on elements that genuinely add value. Include headshots of the actual customer to humanize the story, use dashboards of results to visually represent the data, and add screenshots of any relevant social media posts from the campaigns. If you’re looking to further engage your audience, consider multimedia elements like videos or interactive PDFs that make the content dynamic.

• Use visuals that enhance and complement the narrative and data.
• Include headshots, dashboards, and screenshots from relevant campaigns.
• Incorporate multimedia elements like videos or PDFs to increase engagement.

4. Personalization and audience relevance

We hate to break it to you – but your case study will be ineffective if it lacks relevancy and personalization. Your audience should see themselves in the story you’re telling.

When writing, always consider the specific industry, needs, and preferences of your target readers. The closer the match, the more impactful your case study will be.

If your audience is diverse, you may need to create multiple versions of your case study, each tailored to a different segment. For example, a visually-oriented client might appreciate a design-focused case study, while a data-driven client might prefer one packed with analytics. Personalization shows that you understand their unique challenges and can deliver customized solutions.

Finally, consider how your case study fits into the broader funnel. Readers of your case study are likely already familiar with your business and services. This is where you can really personalize the content to address their specific concerns and move them further along the buyer’s journey.

• Tailor each case study to your specific target audience.
• Create multiple versions for different client types or industries.
• Address specific concerns and demonstrate your understanding of their niche.

Various ways to deliver a social media marketing case study

If you just created an amazing case study that’s sure to knock readers’ socks off, you want people to find it. This means populating every channel at your disposal with your content so your potential customers can’t miss it. 

YouTube social media case study

 Youtube is the second-largest search engine in the world and the platform’s algorithm holds the potential to show your video to a whole new audience. While YouTube’s algorithm is often iffy, writing a catchy title, providing a detailed description, and creating an effective thumbnail are good ways to keep your video in the algorithm’s favor. 

In addition, you’ll want to link your full case study in the comments and get viewers to land on your website. That can be a great starting point for your complex social media campaign.

For example, here’s an Instantly CRM case study on a highly profitable cold email strategy:

General social media case study

If you’re creating a social media case study, using social media to share said case study should be a no-brainer.

 Break down the content of your case study into bite-sized chunks for Instagram or Facebook, post analytics dashboards from the study on Twitter, and link the study to a LinkedIn post to spice up your profile. The shareable nature of social media may lead to your case study going further than just your own site.

Embedded in other types of digital marketing content 

Case studies can also be embedded in other types of content like blog posts, newsletters, guides or ebooks. Go through your current pieces of relevant content and link to your case study to provide extra value. 

For example, Luzmo AI dashboard builder shared their case studies on YouTube, but embedded them in relevant blog posts on their site.

5 winning social media marketing case study examples 

Now that we’ve gone over the components of a winning social media case study, let’s check out some real-world examples. 

1. “How ERA Belgium Provides Great Content for Franchise Businesses with Kontentino,” by Kontentino 

A thing to note regarding this case study is how Kontentino not only highlighted the impressive data but also how the product helped solve a core pain point for ERA Belgium’s franchises .

Highlighted in the middle of the case study is a bold quote from the client that helps solidify Kontentino’s KontentBase product as a must-have tool for franchises. When creating your own case study, consider your product and who’s needs it addresses. Align your customer quotes and data and results reports to match exactly what your target audience is looking for. 

The Konetino case study also includes a CTA at the end so any potential prospects could directly contact the support team.

2. “How an SEO Agency Helped an Artisan Bakery Increase Organic Traffic by 214%,” is a very well written case study by Semrush

This comprehensive case study by Semrush is a perfect example of pinpoint narrative structure and proper formatting. The study flows like a well-written story and guides the reader through the subjects, conflicts and resolutions without a hitch. The tasteful addition of dashboards and bullet points ties the case study up perfectly. 

3. “How Good Dye Young Increased Their Monthly E-commerce Revenue by 305%,” an impressive storytelling case study by Mailchimp 

This case study by MailChimp is full of personality and storytelling. While MailChimp did include impressive numbers, the centerpiece of this case study is the people. The subjects in the case study are referenced casually by their first names, their journey is explored in-depth and there’s no shortage of quotes from them. The imaging MailChimp uses only emphasizes the human side of the relationship between them and the customer. 

4. A set of Capsule CRM Customer Stories

Capsule CRM’s Customer Stories page turns business success into compelling narratives. It’s a showcase of real people achieving great things with the help of Capsule.

From creative startups to financial firms, each story pulls you in with bold visuals and headlines that spark curiosity. These stories give a behind-the-scenes look at how Capsule CRM integrates into different industries, helping clients manage relationships, streamline operations, and grow their businesses.

The message is clear: these companies made it work with Capsule, and so can you. At the end of each story, a call to action awaits, inviting readers to start their own journey.

5. Short and crisp – Localazy Case Studies

Localazy’s Case Studies go beyond highlighting results, focusing on the specific features that brought those successes to life.

They detail how companies like digital business card creators and real estate platforms easily solved their localization challenges. Localazy’s intuitive interface and translation management tools make expanding into global markets feel simple.

These case studies offer a behind-the-scenes view into how businesses use Localazy to grow and thrive, showcasing the platform as a vital tool for managing continuous localization efforts across diverse industries.

Keeping your social media strategy on track with your social media case study 

So now you’ve got a solid idea of what a comprehensive case study should include and you’ve seen the techniques we’ve covered in action. Now it’s time to go over a full template to ensure you stay on track when creating your awesome social media case study. 

Social media marketing case study template 

Outline: Case Study Title

Customer: Customer’s full name 

Company: Company’s name 

Industry: The industry the customer operates in (if applicable) 

Video: Link to a video version (if applicable)

Author: Author’s name 

Case study title

A short introduction of the customer. 

 Be sure to highlight:

• The customer’s name and a little bit about them.
• Why you and your customer were a perfect fit 
• The key successes your customer had after working with you 

Introduce your customer 

In this section, provide a more in-depth overview of your customer. If it’s an individual, explain the person’s background in the context of your product/service. If it’s a business, talk about the company’s background, industry and any recent successes or milestones they have had. 

Describe the problem 

Explain the challenge or opportunity your customers faced before they did business with you. This could be either a reactive reason (i.e. the customer had an issue that needed to be addressed) or a proactive reason (i.e. there was an untapped potential that was unleashed by working with your business).

Why (Customer Name) Chose (Your Company)

In this section, speak about your customer’s decision-making process. Speak about how they discovered you, your possible competition and what made them ultimately decide to do business with you.

How (Your Company) Responded 

Here, explain what happened once your business started working with your customer. What was addressed first, and why? How did your customer feel about working with you in the early days?

The Results

In closing, speak to the results your customer saw after working with you. This section can be supported by statements, quotes, visuals, graphs, and metrics. Whatever you decide to include, be sure it illustrates how much of an impact your company made on your customer. 

Call-to-Action

Use this section to move your readers down the funnel. Add a CTA that encourages readers to either join your newsletter or get in touch with your sales team.

Key takeaways

• A strong social media strategy is essential for crafting compelling case studies that resonate with your target audience.
• Highlighting success stories in social media campaigns helps build credibility and attract new clients.
• Data-driven case studies are powerful tools for showcasing the effectiveness of social media advertising efforts.
• Creating content that aligns with your client’s goals can significantly boost engagement and conversation with users.
• Case studies should focus on how small businesses leverage different types of social media strategies to achieve their objectives.
• Short paragraphs and clear visuals make your social media marketing case study more accessible and engaging for readers.
• When creating content for case studies, emphasize the specific interests of your audience to keep them engaged.
• Case studies are an excellent way to show how your social media strategy helped promote your client’s brand and generate results.
• Personalize your case studies to demonstrate how your approach can be adapted to different types of businesses and industries.
• Use quotes and real-life examples to make your case study more relatable, allowing your audience to see themselves in the story you’re telling.

Crafting a powerful social media case study is more than just data and stories – you have to show the potential within each success. Your next campaign could be the turning point that shifts the conversation and draws in new opportunities.

Once your case study is ready, use tools like Kontentino to share it strategically across social media channels, where it can reach the right eyes at the right time.

Now it’s your move – what story will you tell next?

What are case studies in social media?

Case studies in social media showcase how a social media campaign or social media marketing strategy helped a business achieve its goals, typically through data, key metrics, and success stories, often improving website traffic or engagement.

What are some examples of case study studies?

Examples of social media case studies include successful social media campaigns where businesses improved website traffic, grew their following, or achieved digital marketing objectives through strategic social media advertising and tailored content creation.

How do you write a case study in social studies?

To write a case study in social media marketing, create content and focus on talking about the challenge, detailing the social media campaign, highlighting key metrics, and sharing the impact the campaign had on the business, all in a clear, concise format.

What are the studies about impacts of social media?

Studies on the impacts of social media often explore how effective social media campaigns influence digital marketing performance, from increasing engagement to driving website traffic and boosting overall brand visibility through targeted social media advertising efforts.

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Step-by-step guide to hypothesis testing in statistics

Hypothesis testing in statistics helps us use data to make informed decisions. It starts with an assumption or guess about a group or population—something we believe might be true. We then collect sample data to check if there is enough evidence to support or reject that guess. This method is useful in many fields, like science, business, and healthcare, where decisions need to be based on facts.

Learning how to do hypothesis testing in statistics step-by-step can help you better understand data and make smarter choices, even when things are uncertain. This guide will take you through each step, from creating your hypothesis to making sense of the results, so you can see how it works in practical situations.

What is Hypothesis Testing?

Table of Contents

Hypothesis testing is a method for determining whether data supports a certain idea or assumption about a larger group. It starts by making a guess, like an average or a proportion, and then uses a small sample of data to see if that guess seems true or not.

For example, if a company wants to know if its new product is more popular than its old one, it can use hypothesis testing. They start with a statement like “The new product is not more popular than the old one” (this is the null hypothesis) and compare it with “The new product is more popular” (this is the alternative hypothesis). Then, they look at customer feedback to see if there’s enough evidence to reject the first statement and support the second one.

Simply put, hypothesis testing is a way to use data to help make decisions and understand what the data is really telling us, even when we don’t have all the answers.

Importance Of Hypothesis Testing In Decision-Making And Data Analysis

Hypothesis testing is important because it helps us make smart choices and understand data better. Here’s why it’s useful:

• Reduces Guesswork : It helps us see if our guesses or ideas are likely correct, even when we don’t have all the details.
• Uses Real Data : Instead of just guessing, it checks if our ideas match up with real data, which makes our decisions more reliable.
• Avoids Errors : It helps us avoid mistakes by carefully checking if our ideas are right so we don’t make costly errors.
• Shows What to Do Next : It tells us if our ideas work or not, helping us decide whether to keep, change, or drop something. For example, a company might test a new ad and decide what to do based on the results.
• Confirms Research Findings : It makes sure that research results are accurate and not just random chance so that we can trust the findings.

Here’s a simple guide to understanding hypothesis testing, with an example:

1. Set Up Your Hypotheses

Explanation: Start by defining two statements:

• Null Hypothesis (H0): This is the idea that there is no change or effect. It’s what you assume is true.
• Alternative Hypothesis (H1): This is what you want to test. It suggests there is a change or effect.

Example: Suppose a company says their new batteries last an average of 500 hours. To check this:

• Null Hypothesis (H0): The average battery life is 500 hours.
• Alternative Hypothesis (H1): The average battery life is not 500 hours.

2. Choose the Test

Explanation: Pick a statistical test that fits your data and your hypotheses. Different tests are used for various kinds of data.

Example: Since you’re comparing the average battery life, you use a one-sample t-test .

3. Set the Significance Level

Explanation: Decide how much risk you’re willing to take if you make a wrong decision. This is called the significance level, often set at 0.05 or 5%.

Example: You choose a significance level of 0.05, meaning you’re okay with a 5% chance of being wrong.

4. Gather and Analyze Data

Explanation: Collect your data and perform the test. Calculate the test statistic to see how far your sample result is from what you assumed.

Example: You test 30 batteries and find they last an average of 485 hours. You then calculate how this average compares to the claimed 500 hours using the t-test.

5. Find the p-Value

Explanation: The p-value tells you the probability of getting a result as extreme as yours if the null hypothesis is true.

Example: You find a p-value of 0.0001. This means there’s a very small chance (0.01%) of getting an average battery life of 485 hours or less if the true average is 500 hours.

6. Make Your Decision

Explanation: Compare the p-value to your significance level. If the p-value is smaller, you reject the null hypothesis. If it’s larger, you do not reject it.

Example: Since 0.0001 is much less than 0.05, you reject the null hypothesis. This means the data suggests the average battery life is different from 500 hours.

7. Report Your Findings

Explanation: Summarize what the results mean. State whether you rejected the null hypothesis and what that implies.

Example: You conclude that the average battery life is likely different from 500 hours. This suggests the company’s claim might not be accurate.

Hypothesis testing is a way to use data to check if your guesses or assumptions are likely true. By following these steps—setting up your hypotheses, choosing the right test, deciding on a significance level, analyzing your data, finding the p-value, making a decision, and reporting results—you can determine if your data supports or challenges your initial idea.

Understanding Hypothesis Testing: A Simple Explanation

Hypothesis testing is a way to use data to make decisions. Here’s a straightforward guide:

1. What is the Null and Alternative Hypotheses?

• Null Hypothesis (H0): This is your starting assumption. It says that nothing has changed or that there is no effect. It’s what you assume to be true until your data shows otherwise. Example: If a company says their batteries last 500 hours, the null hypothesis is: “The average battery life is 500 hours.” This means you think the claim is correct unless you find evidence to prove otherwise.
• Alternative Hypothesis (H1): This is what you want to find out. It suggests that there is an effect or a difference. It’s what you are testing to see if it might be true. Example: To test the company’s claim, you might say: “The average battery life is not 500 hours.” This means you think the average battery life might be different from what the company says.

2. One-Tailed vs. Two-Tailed Tests

• One-Tailed Test: This test checks for an effect in only one direction. You use it when you’re only interested in finding out if something is either more or less than a specific value. Example: If you think the battery lasts longer than 500 hours, you would use a one-tailed test to see if the battery life is significantly more than 500 hours.
• Two-Tailed Test: This test checks for an effect in both directions. Use this when you want to see if something is different from a specific value, whether it’s more or less. Example: If you want to see if the battery life is different from 500 hours, whether it’s more or less, you would use a two-tailed test. This checks for any significant difference, regardless of the direction.

3. Common Misunderstandings

• Clarification: Hypothesis testing doesn’t prove that the null hypothesis is true. It just helps you decide if you should reject it. If there isn’t enough evidence against it, you don’t reject it, but that doesn’t mean it’s definitely true.
• Clarification: A small p-value shows that your data is unlikely if the null hypothesis is true. It suggests that the alternative hypothesis might be right, but it doesn’t prove the null hypothesis is false.
• Clarification: The significance level (alpha) is a set threshold, like 0.05, that helps you decide how much risk you’re willing to take for making a wrong decision. It should be chosen carefully, not randomly.
• Clarification: Hypothesis testing helps you make decisions based on data, but it doesn’t guarantee your results are correct. The quality of your data and the right choice of test affect how reliable your results are.

Benefits and Limitations of Hypothesis Testing

• Clear Decisions: Hypothesis testing helps you make clear decisions based on data. It shows whether the evidence supports or goes against your initial idea.
• Objective Analysis: It relies on data rather than personal opinions, so your decisions are based on facts rather than feelings.
• Concrete Numbers: You get specific numbers, like p-values, to understand how strong the evidence is against your idea.
• Control Risk: You can set a risk level (alpha level) to manage the chance of making an error, which helps avoid incorrect conclusions.
• Widely Used: It can be used in many areas, from science and business to social studies and engineering, making it a versatile tool.

Limitations

• Sample Size Matters: The results can be affected by the size of the sample. Small samples might give unreliable results, while large samples might find differences that aren’t meaningful in real life.
• Risk of Misinterpretation: A small p-value means the results are unlikely if the null hypothesis is true, but it doesn’t show how important the effect is.
• Needs Assumptions: Hypothesis testing requires certain conditions, like data being normally distributed . If these aren’t met, the results might not be accurate.
• Simple Decisions: It often results in a basic yes or no decision without giving detailed information about the size or impact of the effect.
• Can Be Misused: Sometimes, people misuse hypothesis testing, tweaking data to get a desired result or focusing only on whether the result is statistically significant.
• No Absolute Proof: Hypothesis testing doesn’t prove that your hypothesis is true. It only helps you decide if there’s enough evidence to reject the null hypothesis, so the conclusions are based on likelihood, not certainty.

Final Thoughts 

Hypothesis testing helps you make decisions based on data. It involves setting up your initial idea, picking a significance level, doing the test, and looking at the results. By following these steps, you can make sure your conclusions are based on solid information, not just guesses.

This approach lets you see if the evidence supports or contradicts your initial idea, helping you make better decisions. But remember that hypothesis testing isn’t perfect. Things like sample size and assumptions can affect the results, so it’s important to be aware of these limitations.

In simple terms, using a step-by-step guide for hypothesis testing is a great way to better understand your data. Follow the steps carefully and keep in mind the method’s limits.

What is the difference between one-tailed and two-tailed tests?

 A one-tailed test assesses the probability of the observed data in one direction (either greater than or less than a certain value). In contrast, a two-tailed test looks at both directions (greater than and less than) to detect any significant deviation from the null hypothesis.

How do you choose the appropriate test for hypothesis testing?

The choice of test depends on the type of data you have and the hypotheses you are testing. Common tests include t-tests, chi-square tests, and ANOVA. You get more details about ANOVA, you may read Complete Details on What is ANOVA in Statistics ?  It’s important to match the test to the data characteristics and the research question.

What is the role of sample size in hypothesis testing?  

Sample size affects the reliability of hypothesis testing. Larger samples provide more reliable estimates and can detect smaller effects, while smaller samples may lead to less accurate results and reduced power.

Can hypothesis testing prove that a hypothesis is true?  

Hypothesis testing cannot prove that a hypothesis is true. It can only provide evidence to support or reject the null hypothesis. A result can indicate whether the data is consistent with the null hypothesis or not, but it does not prove the alternative hypothesis with certainty.

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• Cultivation Theory

What is the Cultivation Theory?

The Cultivation Theory suggests heavy television exposure will have a significant influence on our perception of the real world. The more we see a version of reality being depicted on the screen, the more we will believe it is an accurate reflection of society.

For example, if we watch lots of crime shows and see reports of public disorder on the news bulletins every night, we will begin to worry that violence is having a dangerous impact in our own neighbourhoods. Or, if you watched films set in American high schools, you would be forgiven for believing that American teenagers all look as if they are in the twenties.

With the increasing accessibility of radio and television, many academics and politicians wanted to explore the impact of the media on the public. For instance, the  hypodermic needle theory  and the  two-step flow model  helped to further our understanding of the relationship between the audience and the broadcast media, especially the use of propaganda to spread political ideologies.

In 1973,  George Gerbner , a professor of communication, defined three areas of research:

• institution process analysis – the power roles between the mass media and other organisations;
• message systems analysis – the prevalence and frequency of important symbols used by media texts; and
• cultivation analysis  – the impact of common images on the audience and how they shape our attitudes and beliefs.

A brilliant example of the second focus for analysis of the media is Gerbner’s own  Violence Index , a quantitative look at the representation of violence on primetime television. By simply counting the number of times violence was portrayed in various programmes, Gerbner was able to demonstrate that instances of violence on the television screen occurred more frequently compared to real life.

Mean World Syndrome

The third component of his approach is to evaluate the media’s influence on the audience. Put simply, can television shape our view of the world through the use of common and repetitive messages. Again, Gerbner was able to show heavy viewers, which he defined as someone who watched more than four hours of television per day, were more likely to perceive the real world as violent and dangerous.

Gerbner claimed there was “considerable support for the proposition that heavy exposure to the world of television cultivates exaggerated perceptions of the number of people involved in violence in any given week”.

For example, the following graph is from the “Opinion Research Corporation” which published its results in March, 1979. It provides examples of mainstreaming and resonance in terms of the relationship between the amount of viewing and the per cent of respondents saying that “fear of crime is a very serious personal problem”.

Notice how heavy viewers were more likely to claim violence was a personal problem in their lives compared to those respondents who were considered to be light viewers of television. Put simply, the more violence we are exposed to on the screen, the more we consider violence to be a threat to our own lives.

Gerbner called this cognitive bias  mean world syndrome .

Mainstreaming and Resonance

Since we all watch the same news and follow the same programmes, Gerbner argued that television creates a common ideology and point of view for the audience. Despite any differences in  demographics  and cultural backgrounds, we will begin to share the same values and attitudes. He labelled this filtering effect mainstreaming.

There is often a similarity between everyday reality and the narratives constructed on television. The characters seem convincing and the plots, although exaggerated for dramatic effect, remain believable. If the stories seem real to the audience, we begin to synthesise them into our view of the world. Gerbner labelled this blurring of fact and fiction resonance.

Socialisation

For decades, television has been a pervasive and persuasive influence on society because of its ability to reach such as wide audience. Most people have more than one screen in the house. Therefore, plays an important role in socialisation. Through our continued exposure to the representation of society’s dominant and standard ideologies in the media, or  cumulation , we begin to internalise those values and accept them as truth. For example, gender role stereotypes are well-established, there are obvious constructions of beauty in the media, and junk food is often seen as pleasurable.

Gross and Gerbner called this form of social learning  enculturation .

You might also want to consider Fiske and Hartley’s bardic function of television because they emphasise the importance the media plays in reflecting and reinforcing cultural values and customs. Or Albert Bandura’s social learning theory which included research on the impact television had on our behaviour. The psychologist’s concept of symbolic modelling suggests young people copy the behaviour and attitudes we see on the screen.

Although Gerbner’s Cultural Indicators Project focused on the impact of television on the audience, the cultivation theory can be applied to other media, such as newspapers and YouTube. The model can also be useful for exploring the impact of the representation of other common ideologies and values on our views of the world.

Consider the following examples and the dominant ideologies they express. Can the cultivation theory help explain why we simply accept these  myths ?

It might also be useful to explore these issues in terms of  Cohen’s moral panic concept and Albert Bandura’s social learning theory .

Exam Practice and Revision

The best way to develop your understanding of Gerbner’s cultivation theory is to apply the key concepts to a variety of media texts, issues and debates. You can find examples on our  audience exam practice page , including a question on gender and enculturation which is worth looking at first.

Further Reading

The Classification of Advertisements

Gillian Dyer and Lines of Appeal

The AIDA Principle

Desensitisation and the Media

The Bardic Function

Clay Shirky and the End of Audience

Thanks for reading!

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• bell hooks and Intersectionality
• The Cultural Industries
• Hypodermic Needle Theory
• Two-Step Flow Theory
• Stuart Hall’s Reception Theory
• Abraham Maslow
• Uses and Gratifications
• Moral Panic
• Camera Shots
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Watch CBS News

Fake news, social media, and "The Death of Truth"

By Ted Koppel

Updated on: September 8, 2024 / 10:24 AM EDT / CBS News

We live in an age of alternate facts. More and more Americans are getting their information almost entirely from outlets that echo their own political point of view. And then, of course, there's social media, where there are few (if any) filters between users and a wide world of misinformation.

For example: On July 13 a sniper came within inches of assassinating Donald Trump as he addressed an outdoor rally in Pennsylvania. Within minutes, social media was alive with uninformed speculation. One woman posted, "Who did it?  I bet you it was the government themselves. They're all on the same side."

Koppel said, "We have no idea who she is, she has no particular credibility. Why should I even care that she is out there?"

"Because she could potentially have an audience," said journalist and author Steven Brill. "If the algorithm gives it steam, that could be seen by millions of people."

And then on X (formerly Twitter), this message: "You're telling me the Secret Service let a guy climb up on a roof with a rifle only 150 yards from Trump? Inside job." That message has seven million views and counting.

Brill said, "We're at a point where nobody believes anything. Truth as a concept is really in trouble.  It's suspect."

• Misinformation and conspiracy theories swirl in wake of Trump assassination attempt

The cumulative impact of the lies and distortions just keeps growing, such that Brill titled his new book "The Death of Truth." "There are facts," he said, "and it used to be in this world that people could at least agree on the same set of facts and then they could debate what to do about those facts."

But we're losing our grip on any sort of shared reality. Brill's company, NewsGuard, is attempting to put the brakes on. Its 40 or so staffers around the world identify and rate the credibility of online news and information sources.

It's a finger in the dike, because there's no price to be paid. Almost 30 years ago, the federal government decided that internet platforms were like the phone company. You can't sue the phone company for what a caller might say in a phone conversation.

Brill said, "They inserted a three-paragraph section called Section 230, which said that these [internet] publishers would not be responsible for anything that was published in their chat rooms."

Instead, it left the internet essentially without any enforceable rules. Social media companies exercise only limited control, permitting lies, fake news and intentionally divisive content to proliferate.

The torrent of allegedly Moscow-backed content provoked an angry reaction from the U.S. this past week.

• U.S. says Russia funded media company that paid right-wing influencers millions for videos
• U.S. accuses Russia of sprawling election interference campaign, seizes dozens of fake sites
• How China and Russia fight a propaganda war with the U.S.

But most of the damage is home-grown, from national and supposedly local outlets. "There are more fake news sites posing as legitimate local news in the United States than there are news sites of legitimate local newspapers," said Brill. "There is no monopoly on virtue from either side here. Just to take an example, the most effective fake local news sites are financed by liberal political action committees. And they're sort of especially self-righteous about it. When I interviewed them, they basically said, 'Well, the other guys do it, so we'll do it.' But it's undermining democracy."

• How to spot misinformation: 5 tips from CBS News Confirmed
• How to spot AI and disinformation in 2024 election

And then, Brill points out, we're just beginning to come to terms with the full potential of artificial intelligence. Note that none of these images is real:

Brill said, "It disorients everything, because you don't know if something is a hoax, or is political propaganda, or is a deep fake. You just don't know what to believe."

• Falsehoods about Kamala Harris' citizenship status, racial identity resurface online

Koppel asked, "In the environment you describe, is it possible for us to have a clean, fair, universally-acceptable election?"

"Your last condition is the one that is, I think, impossible – universally acceptable," Brill replied. "Forget universally, even modestly acceptable. I have a real fear that one way or another, regardless of the outcome, that the chaos and the disbelief and anger that's going to prevail on November 6, the day after the election, is really going to put our country to the test."

      READ AN EXCERPT:  "The Death of Truth" by Steven Brill

      For more info:

• "The Death of Truth: How Social Media and the Internet Gave Snake Oil Salesmen and Demagogues the Weapons They Needed to Destroy Trust and Polarize the World – and What We Can Do " by Steven Brill (Knopf), in Hardcover, eBook and Audio formats, available via  Amazon ,  Barnes & Noble  and  Bookshop.org

        Story produced by Dustin Stephens. Editor: Ed Givnish.

      See also:

• Creating a "lie detector" for deepfakes ("Sunday Morning")
• Faceoff against Facebook: Stopping the flow of misinformation ("Sunday Morning")
• Inside the "troll factory" at the center of Russia's election meddling campaign ("CBS Evening News")
• Read the social media posts Russians allegedly used to influence 2016 election cycle
• Misinformation
• Social Media
• Artificial Intelligence

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