The Hidden Influence Behind a Teenager’s Feed

By: Yusra Asad

In the past decade, social media has become an atmosphere for adolescents to learn, socialize, and experiment with their personal identity. Under these videos and recommendations, there is a system of algorithmic personalization that dictates what a teenager sees within fractions of a second. While this system was designed to be a convenience, research shows that it may also exert an inviolable influence over adolescents' mental health (McCrae et al., 2017). As these platforms grow, they increasingly optimize for youth attention. Still, the question grows: Are young social media consumers merelyappealed to proper content, or being deviously shaped by it?

Algorithms function by thoroughly tracking specific patterns: time spent on a post, interaction frequency, and periodic searches. Over time, these systems build personalized profiles to predict what a user is likely to encounter next. Jago (2022) demonstrates that social media platforms like Instagram tend to “track and adapt a user’s activity to custom-tailor their internet experience,” creating a system in which “a controlled, one-sided view of the information flow” gradually forms. Personalized customization isn’t necessarily bad for adolescents. For you pages that are shifted to fit teenagers' interests can help them find communities that fit them. However, the same personalization that was intended for good has led to restrictions on a teenager’s exposure, to the point that it has fabricated insecurities and harmful behavioral patterns (McCrae et al., 2017).

Research on media influence and echo chambers, a society with the same opinions, leaving ignorance within individuals, has associated the restrictive effects of these digital environments with reduced viewpoint diversity and increased cognitive conformity among teenagers. A 2025 systematic review found that algorithms have amplified ideological similarity and that adolescents only have “partial” awareness of how their feeds truly function (Ahmmad et al., 2025). Ignorance of how algorithm effects feeds can develop complications in a teenager's mental and physical health. A dynamic like this creates the circumstance where teenagers are desensitized to emotionally charged and repetitive content without a proper understanding of why it occurs. The effects of this system are more apparent when looking at the mental health data relating to social media. Urvashi Gupta et al. (2025), an assistant professor at District Institute of Education and Training, research uncovers the significant relations between algorithmic exposure and the emotionally negative outcomes among adolescents—including an increase in distress, loneliness, and disrupted sleep. De et al. (2025) support this by underlining that feeds driven solely by the algorithm overstimulate courses of dopamine, creating dependency patterns “analogous to substance addiction.” The anxiety, insecurities, and pressure that adolescents feel aren’t just accidental or unexpected. They’re often the direct result of the algorithmic design. The result of these algorithms, which are built for addiction in teenagers, should lead to extreme, necessary measures to be avoided, as they can directly affect an individual's relationships and long-term mental health.

Depression is a significant result of social media addiction in adolescents. A 2017 published article by McCrae et al. (2017), reviews the social media effect on depressive symptoms in adolescents, McCrae directly states that “frequent internet use raised the risk of depressive symptoms,” the authors correlate the negative impact of addiction in teenagers’ to “younger people with low self-esteem” which has led to various mental health complications, such as chronic loneliness or self induced harm. When teenagers repeatedly encounter peers on social media, studies show that “negative comparisons” occur as a result, which leads to an increase in “the risk of depression” (McCrae et al., 2017). For instance, filters that dramatically alter faces go viral on TikTok, reaching the feeds of multiple groups, specifically teenagers. This algorithmic push on young users' feeds leads to a lack of confidence among them. It provokes an impulse to completely shift their own faces to match what they see on their for you pages; a longing that leads to the excessive use of makeup, skin care, filters, etc. McCrae underlines that young female users are more likely to post “favorable images of themselves” on social media to seek approval, although it tends to result in worsened self-esteem. If teenagers continuously interact with the same videos that create insecurities; algorithm increasingly becomes more harmful, contributing to the decline in adolescents' mental health.

Understanding the effects of algorithms and how they are misused can allow adolescents to navigate social media with more awareness and safety. As algorithms strive to become more sophisticated, digital literacy isn’t just helpful; it is essential for protecting a teenager’s mental health and autonomy. It is vital to continue to look into the changes Meta creates that exploit younger audiences, as companies should be held responsible for any significant harm they cause to their users.

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Word Cited

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Gupta, Dr & Sharma, Ms & Rawat, Dr & Sriram, Nithya & Kumar, Dr & Kumar, Umesh. (2025). Understanding the Impact of Social Media Algorithms on Teenagers’ Brain and Emotions: A Cross-Field Approach. International Journal of Environmental Sciences. 553-559. 10.64252/vmap3080.

Jago, Ethan. 2022. "Algorithmic Manipulation: How Social Media is Shaping our Theology." Liberty Theological Review 6, (1). https://doi.org/10.70623/RRXO9240. Accessed 11 Dec. 2025.

McCrae, N., Gettings, S., & Purssell, E. (2017). Social Media and Depressive Symptoms in Childhood and Adolescence: A Systematic Review. Adolescent Research Review, 2(4), 315–330. https://doi.org/10.1007/s40894-017-0053-4

Vangeli, Marius, et al. The Philosophy of Algorithmic Manipulation Unveiling the Influence of Social Media Algorithms. https://www.diva-portl.org/smash/get/diva2:1770486/FULLTEXT01.pdf. Accessed 11 Dec. 2025.

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