International Journal of Social Science Research (IJSSR)

The Algorithmic Mirror: Instagram Feeds and Female College Students’ Self-Image and Body Satisfaction

The recommendational algorithms employed by Instagram favor attractive and other visually idealized images that increase social comparisons and result in consistent undermining of body satisfaction and self-image by female college students. In this paper, the author will discuss the role of these algorithmic feed in forming self-perception through the lens of Social Comparison Theory, Objectification Theory, and recent research papers published between 2018–2026. Cross-sectional, experimental, and qualitative research indicates that one of the primary causes of body dissatisfaction is an obsessive habit of just window shopping based on the comparisons made with influencers. Some of the elements criticized in the paper include filter bubbles, algorithm support of homogenized standards of beauty, and curating via engagement. Female students in colleges, who are 18-24 years old, are particularly susceptible at this stage of development. A study by revealing that personalized feed increases a loop: the more a user enjoys idealized content, the more content she gets exposed to, to perpetuate negative self-assessments. Recommendations on digital-literacy interventions and platform-design modifications to support content diversity, as well as individual, healthier engagements with social-media, end the paper. The important aspect of addressing the mental-health crisis of young women today is to understand these algorithmic dynamics.