Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.

Journal: Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
PMID: 38366336

Abstract

INTRODUCTION: Instagram is a popular social networking platform for sharing photos with a large proportion of youth and young adult users. We aim to identify key features in anti-vaping Instagram image posts associated with high social media user engagement by artificial intelligence.

Authors

  • Zidian Xie
    Clinical and Translational Science Institute, University of Rochester School of Medicine and Dentistry, 265 Crittenden Blvd CU 420708, Rochester, NY 14642-0708. Email: zidian_xie@urmc.rochester.edu.
  • Shijian Deng
    Department of Computer Science, University of Rochester, Rochester, NY, USA.
  • Pinxin Liu
    Department of Computer Science, University of Rochester, Rochester, NY, USA.
  • Xubin Lou
    Goergen Institute for Data Science, University of Rochester, Rochester, NY, USA.
  • Chenliang Xu
    Department of Computer Science, University of Rochester, Rochester, New York, United States of America.
  • Dongmei Li
    Clinical and Translational Science Institute, University of Rochester School of Medicine and Dentistry, Rochester, New York.

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