Communications in Humanities Research ISSN: 2753-7072
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Research Article

How Big Data Recommendation Algorithms Reinforce Gendered Body Shaming

Xueyinuo LiHangzhou Foreign Language School Cambridge A-Level Center*

* Corresponding author: [email protected]

Abstract

With the rise of social media, the body shaming has evolved from occurring in personal interactions and traditional forms of media to being amplified by algorithm-driven social media platforms. The surge in self-image and beauty-centric social media platforms, such as Instagram and TikTok, fueled by big data recommendation algorithms, significantly impacts users’ self-esteem and the construction of self-image by enforcing rigid beauty standards. This paper focuses on the effects of big data recommendation algorithms and beauty-obsessed and centric social media on body shaming and its psychological and social impacts, seeking solutions to counter the negative impacts of body shaming. The review integrates concepts from media studies, psychology, and computer science to analyze the impact of social media algorithm designs on user behavior and social norms. The findings underscore the need for an intentional shift in social media design, policy frameworks, and public discourse to foster social equity and combat discrimination in the digital environment.

Keywords: Body shaming; Social media; Algorithmic bias; Big data recommendation algorithms; Algorithmic system design
Published: August 27, 2025
DOI: 10.54254/2753-7064/2025.LC26348
Volume: CHR Vol.76
pp. 79-84
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