The Role of Social Media Algorithms in Teen Social Media Addiction
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Social media use has become a fixture in the daily life of most adolescents, holding powerful influence over teens’ self-perception and social identity (De et al., 2025). Research shows that well-developed algorithms employed by social media platforms intentionally lead to increased screen time and, thus, increased addiction rates for many teens (De et al., 2025). Despite the number of studies that show a direct correlation between social media use and teen addiction, “[i]nternal mechanisms like algorithms are hidden from users” (Lawrence, 2022, p. 81). As a result, teenagers are susceptible to falling victim to decisions made by companies that may not prioritize ethical decision-making.
How It Works
Social media platforms employ AI-driven algorithms to increase and extend user engagement for their personal benefit. Many people do not fully understand that “these platforms survive through gathering troves of data on their users and using this data to sell advertisement opportunities to businesses and individuals” (Lawrence, 2022, p. 51). To gather necessary information, companies employ “natural language processing, linear regression, and clustering [to] analyze user behavior” (De et al., 2025, para. 4).
After analyzing the collected data, platforms “recommend tailored content and optimize real-time feeds, increasing user engagement and fostering addictive behaviors” (De et al., 2025, para. 4). According to De et al. (2025) (See Figure 1), when screen time is maximized, the brain’s reward centers are more deeply activated. Consequently, “[t]his cycle of optimized content and heightened engagement accelerates the development of addictive behaviors. The interplay between altered brain physiology and AI-driven content optimization creates a feedback loop that promotes social media addiction among teenagers” (De et al., 2025, para. 1).
Figure 1
Adolescents are especially vulnerable to these strategies, as is further explained in the video “Why scrolling on social media is addictive” published by The Washington Post (2023). Effects of internet addiction can actually change the development of the brain, lower attention spans, impair cognitive function, and increase the likelihood of high-risk behavior (De et al., 2025, para. 9).
Who’s in Control?
The use of these algorithms is widely viewed as unethical, as social media platforms aspire to increase use for their own gain. More and more, websites use content marketing to increase profit margin, and social media platforms are no exception. There is little oversight, other than standards set by individual companies. As noted by Lawrence (2022), “when organizations regulate themselves, we can easily see abuses and overreaches of power and ethical problematics” (p. 91). This is dangerous considering the far-reaching impact websites have and their ability to spread misinformation and manipulate users. For this reason, more than forty states have joined forces in a lawsuit accusing Meta of intentionally employing features that increase the risk of addiction (De et al., 2025).
The advanced algorithms used by social media platforms change frequently, making it difficult for the average user to understand the process. As argued by Lawrence (2022), people have the right to gain insight into the inner workings of these platforms, especially when it pertains to matters that may impact their mental health and cognitive development. Platforms should be more transparent in educating users on what data is used to manipulate their feed, especially considering that they often target teens by “pushing harmful diet strategies by influencers, deepfake videos, extremist material, or content dealing with mental health. Inevitably, that only feeds anxieties and turbocharges anxiety and depression” (De et al., 2025, para. 5). If social media platforms are designing algorithms to increase use, and increased use increases the risk of addiction, there should be a call for transparency to protect adolescent users.
The Path Forward
More users are joining social media daily, and adolescents currently make up a third of the more than five billion users (De et al., 2025, para. 1). To counter the addictive nature of social media, an increased and united effort to educate all users on the negative effects of use is needed. The following actions should be considered:
· Teens should engage in small group discussions on their use.
· Parents should be provided information on healthy usage guidelines for
adolescents.
· Schools should offer digital literacy education in elementary school.
· Social media platforms should be more transparent in their use of algorithms.
· Government officials should commit to understanding and preventing the
dangers of social media.
As noted by Lawrence (2022), “[i]t is up to us to be good stewards of technology, philosophy, and ethics, and to deeply consider what it is that we will be doing with Internet-based networking and communication platforms into the future” (p. 50). With a concerted effort, we can examine and improve the way social media is used in our society.
References
De, D., El Jamal, M., Aydemir, E., & Khera, A. (2025, January 8). Social media algorithms and teen addiction: Neurophysiological impact and ethical considerations. Cureus. https://pmc.ncbi.nlm.nih.gov/articles/PMC11804976/
Lawrence, D. (2022). Digital writing: A guide to writing for social media and the web. Broadview Press.
Washington Post. (2023, July 14). Why scrolling on social media is addictive [Video]. YouTube. https://youtu.be/rooEBjZWpDc?si=ghXSuvmq6XQUzpz1
Jennifer,
ReplyDeleteI do agree with your post and found it very interesting. I think as educators, parents, and users ourselves, we know this exists, but to such an extent is scary. I agree with Lawrence (2022) that it is we are the ones who have to educate ourselves, but I think it is incumbent on educators and parents to constantly remind students how to use technology properly.
Poth (2023) shares why it is important for educators to model appropriate behavior and even show students when they make mistakes. What this shows our students is that there are benefits to using social media, and there is a lot that can be gained from having access to instant information, but there are also several pitfalls.
References
Lawrence, D. (2022). Digital writing: A guide to writing for social media and the web. Broadview Press.
Poth, R.D. (2023, November 16). Developing students’ digital citizenship skills:
Teaching students to develop an awareness of data security, online etiquette, and cyberbullying helps them make better decisions online. Edutopia.https://www.edutopia.org/article/teaching-digital-citizenship-skills/
Jennifer, thanks so much for this timely and well-researched blog post. The conversation around recognizing social media’s impact on students’ brain development, and for holding developers accountable for their role, will only grow louder as social media use becomes an increasingly integrated part of 21st-century education. Lawrence (2022) points out that much of social media’s revenue model depends on content consumption driven by sophisticated data analysis and marketing strategies and their “primary objective is not to provide the most truthful, relevant, or highly vetted sources to you” (p. 136). While we cannot stop our students from engaging in social media, we can equip them to understand it better. In Finland, researchers designed a tool for a digital literacy class that helps students understand the very mechanisms you described: algorithms, data collection, and engagement strategies, taught through an interactive, Instagram-style interface. The tool gives students real-time feedback behind how their actions influence what they and others see, helping them build AI literacy and awareness of how these platforms shape their experiences (Pope et al., 2024). I doubt anyone would argue against the need for digital literacy classes, but you make a strong case that students should also be taught how these companies operate behind the scenes, and I take heart that something is being developed!
ReplyDeleteReferences
Lawrence, D. (2022). Digital writing: A guide to writing for the web. Connected Learning.
Pope, N., Kahila, J., Vartiainen, H., Saqr, M., López-Pernas, S., Roos, T., Laru, J., & Tedre, M. (2024). An XAI social media platform for teaching K–12 students AI-driven profiling, clustering, and engagement-based recommending. arXiv. https://doi.org/10.48550/arXiv.2412.13554