NOT CLICKBAIT?! Content creation is a trap

Can creators retain their integrity in a system that rewards virality?

Content creation is a trap. As a content creator with over 40,000 followers on TikTok who seeks to share my knowledge, it was made clear to me early on that my role is as an entertainer first and as an educator second. Viewers’ natural tendencies demand as much because of two cognitive biases. First, confirmation bias entails that we engage with and believe in information we already think, more than that which we are unfamiliar with. Negativity bias, on the other hand, dictates that humans respond more strongly to threats and scandals than they do to neutral or even positive information. When these behavioral mechanisms are fed into an algorithm designed to prioritize reactions and engagement, extreme, negative, and conformist content naturally arises as the winners of machine-driven selection.

Sensationalism, the tactic through which content is intentionally exaggerated or distorted to provoke strong emotional reactions, reigns supreme as the easiest way to fame. It is no surprise, then, that research has found that platforms like Instagram have increased the exposure of negative emotional content by 23%.¹ This forced me to grapple with a disturbing problem: if I sought to inform, how could I reach more viewers without simultaneously distorting the truth to elicit stronger reactions? The dilemma of a content creator is deciding the price of their integrity in the face of virality. There is, however, a way to cheat that price—if one is willing to get a bit creative.

Photo by Sirisvisual / Unsplash

Before even beginning to cheat the system, however, a content creator must first understand the principles they aim to defend. The temptation to seek engagement at any cost is all too easy to give in to; you can find videos of people screaming at trees, which gain millions of views due to the sheer absurdity of the content. This temptation indicates the first barrier to using social media as a platform to benefit society: understanding the social responsibility that comes with the power of reach. The first component of this awareness is realizing the cost of time that content charges viewers.

On TikTok, video analytics display the total watch time for any posted video. My most popular video has 412,513,000 seconds of watch time, or roughly more than 13 years of accumulated watch time—all for a one-and-a-half-minute-long video. I realized the gravity of my reach then. I took 13 years’ worth of time away from society—was what I gave in exchange worth it? While entertainment in itself isn’t harmful, I grounded myself in the desire to create content that delivers value to people in exchange for their time. That, however, led me to another question: what exactly is a content creator’s role in society, and when is content worth watching?

The second component of this social responsibility is understanding the very real effects content has on society. Every person has schemas, or mental models that organize and interpret information, shaping how they perceive the world around them.² When one imagines a cat, for example, related information might come to mind: cats have fur, four legs, whiskers, a tail, and so on. Those schemas are malleable if additional information is provided, and that is where the true danger begins.³ Imagine being pushed information for years that creatures that meow and have whiskers are, in fact, dogs—one might even start to believe it. Through a phenomenon called the illusory truth effect, human minds are structured to believe statements the more frequently they encounter them, even if they aren’t true or accurate.⁴^,⁵ This means viewers’ perceptions of reality aren’t determined by the veracity of information, but by how often the algorithm chooses to push certain content.

One can think they are in control of what they watch, but their preferences have often already been shaped by previous content. This is the logical endpoint of the illusory truth effect: after prolonged exposure to consistent media messages, people’s schemas change to mirror them—a phenomenon described in cultivation theory. This is dangerous when algorithms are designed to push content that feeds into people’s negativity and confirmation biases because it means algorithms are positioned and structured to alter people’s perceptions of reality in harmful ways.⁶ A direct example of this is TikTok’s personalized recommendations resulting in a strong correlation between adolescent anxiety symptoms and eating disorder behaviors.⁷ In the context of important sociopolitical issues, this can lead to political alienation and echo chambers that have significant impacts on voter turnout, political sentiments, and agenda-setting on a national level.⁸^,⁹ This is the true responsibility of the content creator: with the power to shape people’s perceptions of reality comes an obligation to use the power of reach to effect positive social change. Otherwise, one would become complicit in a system already poised to harm society.

How can a system that rewards negativity and echo chambers be cheated to effect positive social change, then? The key is striking a balance between utilizing different cognitive biases while still exercising moderation. Problems arise when emotions are provoked by misrepresentations and lead to bad outcomes, but that isn’t the only way to evoke powerful responses from viewers. Negative content is harmful when it breeds learned helplessness, such as by permanently degrading people’s trust in democratic institutions or when it exaggerates the risks of long-term crises to scare viewers into engagement.¹⁰ However, important pieces of news and knowledge can still be negative and elicit strong reactions while leading to positive social change.

If the algorithm rewards negativity, truthfully reporting on corruption or war can still engage viewers, and positive social change can be effected by providing clear calls to action to avoid learned helplessness. In other cases, representing diverse perspectives to mitigate the risk of echo chambers or providing clear paths to resolution can also reduce panic. Social media is inherently interactive, and while engagement can be solicited by replying to comments and following trends, the burden is also on content creators to broach new topics and avoid echo chambers. Inherently valuable information should always be able to elicit engagement if it matters, and the art of content creation is discovering an angle that makes knowledge both relatable and useful without distorting or exaggerating it.

The path content creators take to retain their integrity lies not in rejecting the algorithm, but in refusing to let it dictate their values. Algorithms are powerful because they find the most efficient ways to use human behavior for engagement, but they fail to discern between outrage from information and outrage from manipulation. The responsibility of the content creator is to make that distinction for the algorithm and find creative ways to deliver the truth without succumbing to sensationalism.

Content creation is still a trap. There will always be the temptation to sacrifice nuance for engagement, and there will always be creators willing to pay that price and take the easy way out. Integrity, then, goes beyond a price to be paid for virality; it is a conscious decision to refuse to sacrifice the truth for engagement every time we press the “post” button. If every scroll shapes how someone understands the world, then every upload is an ethical decision. The challenge for content creators is to rise to that responsibility and prove that the truth is compelling enough to win without abandoning itself.

Bibliography

Cinelli, Matteo, Gianmarco De Francisci Moreales, Alessandro Galeazzi, Walter Quattrociocchi, and Michele Starnini. 2021. “The Echo Chamber Effect on Social Media.” Proceedings of the National Academy of Sciences 118 (9): e2023301118. https://doi.org/10.1073/pnas.2023301118.

Fagan, Abigail. 2025. “Illusory Truth Effect.” Psychology Today. November 12, 2025. https://www.psychologytoday.com/us/basics/illusory-truth-effect.

Hu, Ziye. 2025. “Research on the Impact of Social Media Algorithmic on User Decision-Making: Focus on Algorithmic Transparent and Ethical Design.” Applied and Computational Engineering 174: 18–22. https://doi.org/10.54254/2755-2721/2025.PO24665.

McLeod, Saul. 2026. “Piaget’s Theory of Cognitive Development.” Simply Psychology. January 23, 2026. https://www.simplypsychology.org/piaget.html.

Organisation for Economic Co-operation and Development. 2024. OECD Survey on Drivers of Trust in Public Institutions—2024 Results: Building Trust in a Complex Policy Environment. Paris: OECD Publishing. https://doi.org/10.1787/9a20554b-en.

Perera, Amanda. 2026. “Cultivation Theory in Media Communication.” Simply Psychology. May 18, 2026. https://www.simplypsychology.org/cultivation-theory.html.

Ye, Steeven, David Attali, Maria Ghazi, Arnaud Cachia, Mathieu Cassotti, and Grégoire Borst, “Systematic Review and Meta-Analysis of the Evidence for an Illusory Truth Effect and Its Determinants,” Nature Communications 17 (2026): Article 3270, https://doi.org/10.1038/s41467-026-70041-x

1. Hu, Ziye. 2025. “Research on the Impact of Social Media Algorithmic on User Decision-Making: Focus on Algorithmic Transparent and Ethical Design.” Applied and Computational Engineering 174: 18–22. https://doi.org/10.54254/2755-2721/2025.PO24665.

2. McLeod, Saul. 2026. “Piaget’s Theory of Cognitive Development.” Simply Psychology. January 23, 2026. https://www.simplypsychology.org/piaget.htmltheory, after.

3. Ibid.,

4. Fagan, Abigail. 2025. “Illusory Truth Effect.” Psychology Today. November 12, 2025. https://www.psychologytoday.com/us/basics/illusory-truth-effect,.

5. Ye, Steeven, David Attali, Maria Ghazi, Arnaud Cachia, Mathieu Cassotti, and Grégoire Borst, “Systematic Review and Meta-Analysis of the Evidence for an Illusory Truth Effect and those messages—a phenomenon described inIts Determinants,” Nature Communications 17 (2026): Article 3270, https://doi.org/10.1038/s41467-026-70041-x

6. Hu, Ziye. 2025. “Research on the Impact of Social Media Algorithmic on User Decision-Making: Focus on Algorithmic Transparent and Ethical Design.” Applied and Computational Engineering 174: 18–22. https://doi.org/10.54254/2755-2721/2025.PO24665.

7. Ibid., 18–22.

8. Organisation for Economic Co-operation and Development. 2024. OECD Survey on Drivers of Trust in Public Institutions—2024 Results: Building Trust in a Complex Policy Environment. Paris: OECD Publishing. https://doi.org/10.1787/9a20554b-en.

9. Cinelli, Matteo, Gianmarco De Francisci Moreales, Alessandro Galeazzi, Walter Quattrociocchi, and Michele Starnini. 2021. “The Echo Chamber Effect on Social Media.” Proceedings of the National Academy of Sciences 118 (9): e2023301118. https://doi.org/10.1073/pnas.2023301118.

10. Organisation for Economic Co-operation and Development. 2024. OECD Survey on Drivers of Trust in Public Institutions—2024 Results: Building Trust in a Complex Policy Environment. Paris: OECD Publishing. https://doi.org/10.1787/9a20554b-en.