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Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54433, first published .
Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach

Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach

Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach

Journals

  1. Ahmad M, Sidorov G, Amjad M, Ameer I, Batyrshin I. Opioid Crisis Detection in Social Media Discourse Using Deep Learning Approach. Information 2025;16(7):545 View
  2. Wojciechowski T. Social Learning Theory and Gateway Hypothesis as a Causal Pathway Linking Rule-Breaking Peer Association to Marijuana Use via Nicotine Vaping. Journal of Psychoactive Drugs 2026:1 View
  3. Nguyen V, Le H, Le G, Mai A, Nguyen T. Artificial intelligence innovations in substance use prevention on social media: A scoping review. Public Health 2026;254:106200 View
  4. Lu L, Yu X, Xu Z, Kwon H, Reddy A, Xin H, Zhang S, Yang E, Li Y, Yang S. Foodie traps within facebook cannabis promotional posts: Deploying multimodal deep learning AIs to monitor audience engagement. Drug and Alcohol Dependence 2026;283:113128 View

Books/Policy Documents

  1. Fernández-López L, Martínez Laorden E, Martín Sánchez F, Almela Rojo P, Navarro-Zaragoza J. Substance Abuse - New Compounds and New Problems. View

Conference Proceedings

  1. Yuan Y, Zhang J, Aledavood T, Zhang R, Saha K. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Lens View