Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72822, first published .
Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community–Related Posts on Social Media: Quantitative Study

Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community–Related Posts on Social Media: Quantitative Study

Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community–Related Posts on Social Media: Quantitative Study

Thu T Nguyen   1 * , SCD, MSPH ;   Xiaohe Yue   1 * , MS ;   Heran Mane   1 * , BS ;   Kyle Seelman   2 * , BS ;   Penchala Sai Priya Mullaputi   1 * , MS ;   Elizabeth Dennard   1 * , MPH ;   Amrutha S Alibilli   1 * ;   Junaid S Merchant   1 , MS, PhD ;   Shaniece Criss   3 * , MPH, MPA, SCD ;   Yulin Hswen   4 * , MPH, SCD ;   Quynh C Nguyen   1 , MSPH, PhD

1 Department of Epidemiology and Biostatistics, University of Maryland, College Park, College Park, MD, United States

2 Department of Computer Science, University of Maryland, College Park, College Park, MD, United States

3 Department of Health Sciences, Furman University, Greenville, United States

4 Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, United States

*these authors contributed equally

Corresponding Author:

  • Thu T Nguyen, SCD, MSPH
  • Department of Epidemiology and Biostatistics
  • University of Maryland, College Park
  • 4254 Stadium Dr.
  • College Park, MD 20742
  • United States
  • Phone: 1 301-405-6589
  • Email: ttxn@umd.edu