- Title
- BigTokDetect: A Clinically-Informed Vision–Language Modeling Framework for Detecting Pro-Bigorexia Videos on TikTok
- Creators
- Minh Duc Chu - USC Information Sciences Institute, United StatesKshitij Pawar - USC Information Sciences Institute, United StatesZihao He - USC Information Sciences Institute, United StatesRoxanna Sharifi - Keck School of Medicine, USC, United StatesRoss Sonnenblick - Department of Clinical Psychology, Drexel University, United StatesMagdalayna Curry - Annenberg School for Communication and Journalism, USC, United StatesLaura D’Adamo - Drexel University, Center for Weight, Eating and Lifestyle Science (WELL) [Historical]Lindsay Young - Annenberg School for Communication and Journalism, USC, United StatesStuart B. Murray - Department of Psychiatry and Biobehavioral Sciences, UCLA, United StatesKristina Lerman - USC Information Sciences Institute, United States
- Publication Details
- EACL 2026 - 19th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, Vol. 1 - (Long Papers), v 1, pp 766-790
- Publisher
- Association for Computational Linguistics
- Number of pages
- 25
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Scopus ID
- 2-s2.0-105040521799
- Other Identifier
- 991022195747404721
Conference proceeding
BigTokDetect: A Clinically-Informed Vision–Language Modeling Framework for Detecting Pro-Bigorexia Videos on TikTok
EACL 2026 - 19th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, Vol. 1 - (Long Papers), v 1, pp 766-790
2026
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