Health Issues Linked to Skinny Girl Videos in Internet Culture

Friday, 20 September 2024, 16:04

Health concerns are on the rise due to the proliferation of skinny girl videos influencing internet culture. Particularly controversial is Liv Schmidt, whose tips on achieving a 'skinny' lifestyle have gathered significant attention. With videos targeting weight loss and emotional eating, her community of followers has sparked debate over health implications and body image standards.
Fastcompany
Health Issues Linked to Skinny Girl Videos in Internet Culture

The Impact of Skinny Girl Videos on Health

Across social media, influencers have gained massive followings by promoting weight-related tips that often advocate for a 'skinny' ideal. One notable figure is Liv Schmidt, who attracted 670,000 followers with her videos focusing on skinny girl essentials. Her content included strategies like how to avoid the freshman 15 and how to stop emotional eating during work hours, frequently accompanied by animal emojis depicting various sizes.

Account Deletion and Controversy

However, Schmidt's approach led to her TikTok account's removal on September 17 for violating community guidelines. A TikTok spokesperson confirmed that her account was deleted due to reports from users who accused her of weight shaming and rage-baiting. Discussions on platforms like Reddit have seen users claim responsibility for this action, emphasizing the potential harm her content may cause.

The Broader Effects on Health and Internet Culture

  • Rising concerns over body image standards influenced by popular figures.
  • The impact of social media on mental health regarding weight.
  • Shifting community guidelines and their enforcement on platforms.

As the conversation continues, many are advocating for healthier representations of body image across social media to protect vulnerable audiences.


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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