Rise of the Angertainment Economy

Why is there so much outrage in our modern world? Because the internet and social media don't have subscription fees. ... Wait, what?

So, it's not your data that's really the valuable asset; it's your attention (e.g., attention economy). However, what you are really giving up with free service is your mental health and stable society. Attention doesn't necessarily provoke action without an emotional response. Research shows that anger increases actions such as sharing a post significantly. So, the algorithms increase views of anger outrage posts which often go viral.

Politicians and news media became aware of this and have capitalized on the angry train. Politicians get elected to troll the "other side" not create policy now. News starts every story with statements like "this will make your blood boil." We effectively live in what many call the 'outrage economy'. This undermines the stability and security of our modern civilization. Next time you bash a subscription-based model, perhaps calculate that into your consideration. This is really a story of unintended bad incentives.

Research has explored the relationship between social media algorithms and the anger-based media economy, shedding light on their impact.

One insight relates to confirmation bias and filter bubbles. Algorithms personalize content based on user preferences, creating filter bubbles reinforcing existing beliefs. This can contribute to polarization and increase exposure to anger-inducing content aligned with users' views. (See: Pariser, E. (2011). The filter bubble: What the Internet is hiding from you.)

Think about it from a social media perspective for a moment. How do emotional contagion and engagement increase the value of a post or story? Algorithms prioritize emotionally engaging content, including anger. This is because emotionally charged content generates more user engagement, such as likes, comments, and shares. Anger-based media can spread rapidly and reach a wider audience. (See: Kramer, A. D., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks.)

Most understand the concept of clickbait and sensationalism. Algorithms optimizing for engagement can incentivize clickbait and sensationalized content. Provocative headlines, conspiracy theories, and controversial opinions attract attention, resulting in higher visibility within the platform. (See: Llewellyn, D., & Ananny, M. (2019). Auditing the news feed: Algorithms’ impact on news diversity. Digital Journalism, 7(6), 774-794.)

One of the primary problems online stems from the human propensity for addictive behaviors and prolonged usage of apps or social media. Gamification elements in social media platforms and algorithms prioritizing engagement contribute to addictive behaviors. Anger and outrage can drive prolonged platform usage as users become emotionally invested. (See: Fardouly, J., Diedrichs, P. C., Vartanian, L. R., & Halliwell, E. (2015). Social comparisons on social media: the impact of Facebook on young women's body image concerns and mood.)

Algorithms used by social media platforms can contribute to the anger-based economy in several ways, including content prioritization, increased polarization, an arms race of sensationalism, and gamification keeping us captive.

Content Prioritization

Social media algorithms are designed to maximize user engagement and time spent on the platform. They analyze user data and behavior to determine what content to prioritize in individuals' feeds. Algorithms often favor content that generates strong emotional reactions, such as anger, because it tends to elicit more engagement, comments, and shares. As a result, anger-inducing content is more likely to be shown to users, creating a feedback loop that perpetuates the spread of such content.

Echo Chambers and Polarization

Social media algorithms personalize content based on user's preferences and behavior, creating filter bubbles or echo chambers. These bubbles often reinforce users' existing beliefs and biases, presenting them with content that aligns with their views. When anger-based content is favored by the algorithm, it can further polarize users by amplifying extreme perspectives and suppressing more moderate or balanced content. This can lead to increased anger, divisiveness, and the spread of misinformation.

Sensationalism

Algorithmic systems are highly responsive to user interactions, such as clicks, likes, and shares. This incentivizes content creators to generate sensationalized and provocative headlines or thumbnails to attract attention. Anger-inducing content, often in the form of sensationalized news, conspiracy theories, or controversial opinions, tends to be more clickable and shareable, thus gaining higher visibility within the platform. The algorithm's focus on engagement metrics encourages producing and disseminating such content, even if it lacks factual accuracy or context.

Gamification Using Human Addiction

As mentioned earlier, social media platforms employ various gamification techniques, such as likes, comments, and followers, to encourage user engagement and addiction. The algorithms are designed to optimize for these engagement metrics, rewarding content that generates a strong user response. Anger and outrage are powerful emotions that can drive high levels of engagement, leading to addictive behaviors and prolonged platform usage. Consequently, the algorithm promotes anger-based content to retain users' attention and maximize ad revenue.

It's important to note that the algorithms themselves are not inherently malicious but rather a reflection of user preferences and the business models of social media platforms. The primary goal of these algorithms is to keep users engaged and generate revenue, often leading to unintended consequences like the amplification of anger-based media. However, platform companies are increasingly recognizing the negative impacts and taking steps to address these issues by adjusting algorithms, implementing content moderation policies, and promoting more diverse and balanced content.

Research Shows News Headlines Have Gotten More Negative

Longitudinal analysis of sentiment and emotion in news media headlines using automated labelling with Transformer language models

See the data trends below:

We must consider reversing this self-destructive trend and creating a better system based on incentives for accurate journalism, open discourse, and truth-seeking media.

#cyberpsychology #outrage #angertainment #cogsec #cognitivescience