The rise in eating disorders, a dangerous mental health condition with high mortality and morbidity, has been linked to the proliferation of idealized body images on social media. However, the link between social media and eating disorders is far more complex. We argue that social media platforms create a feedback loop that amplifies the growth of content and communities that promote eating disorders like anorexia and bulimia. Specifically, social media platforms make it easy for vulnerable individuals to find and connect to like-minded others, while group dynamic processes encourage them to stay engaged within communities that promote and glorify harmful behaviors linked to eating disorders. We characterize this dynamic empirically through a combination of network and language analysis. We describe a novel framework that leverages large language models to analyze the discourse within online communities and probe their attitudes on topics related to eating disorders to identify potentially harmful content. Our work emphasizes the need for better social media moderation to disrupt harmful feedback loops and protect vulnerable individuals.

翻译：饮食失调是一种具有高死亡率和高发病率的危险心理健康状况，其增长与社交媒体上理想化身体形象的泛滥密切相关。然而，社交媒体与饮食失调之间的联系远比想象中复杂。我们认为，社交媒体平台形成了反馈循环，加剧了宣扬厌食症和贪食症等饮食失调的内容和社区的扩张。具体而言，社交媒体平台使易感个体能够轻松找到并联系志同道合者，而群体动态过程则促使他们持续参与那些宣扬并美化与饮食失调相关的有害行为的社区。我们通过网络分析与语言分析的结合，对这一动态进行了实证刻画。我们描述了一个新颖框架，利用大语言模型分析在线社区的论述内容，并探查其对饮食失调相关话题的态度，从而识别潜在的有害内容。本研究强调了优化社交媒体监管的必要性，以打破有害反馈循环并保护易感个体。