Community Conversations with Cornell Tech: Eden Shaveet

Short-form video platforms like TikTok and Instagram Reels are among the most widely used social media platforms across all age groups, especially among adolescents and young adults. Designed to sustain engagement through low-friction interaction features and reward-driven feedback loops, these platforms have been linked to compulsive scrolling and diminished self-regulation. For users with behavioral health conditions, such as body image disturbance (BID)-driven eating disorders, the platforms’ inferred-interest signals often reflect underlying pathology, and the content served in response can exacerbate symptoms. Short-form video platforms are among the most preferred social media platforms for young people with eating disorders, yet users with eating disorders are algorithmically served over 4,000% more pro-eating-disorder content, a disparity linked to worsening symptoms.

In this talk, Eden Shaveet, a Ph.D. student at Cornell Tech, will discuss her ongoing research on intervening in multimedia-exacerbated symptomatology, understanding both the stimulus (the content consumed by a user) and the response (the user’s reaction to it). She will present her work on novel approaches to data collection and processing for adaptive content moderation, physiological sensing for fixation detection and interruption, and future directions for this research.

No registration required. This program is held in partnership with Cornell Tech at the Roosevelt Island Library.

DISCLAIMER: This presentation by Cornell Tech is for informational purposes only and does not constitute medical advice. The New York Public Library (the "Library") does not provide medical advice or endorse any medical service provider or the services they provide. You should always conduct your own due diligence when selecting a medical provider. The Library is not responsible for (i) the reliability, timeliness, or accuracy of the information provided in this presentation, or (ii) the security or privacy of any information you provide to Cornell Tech or any other third-party service provider.