This paper is in the following e-collection/theme issue:

Public (e)Health, Digital Epidemiology and Public Health Informatics (861) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1789) Natural Language Processing (801) Infoveillance and Social Listening (252) Social Media in Public Health informatics (52) Smoking and Vaping in Adolescence (33)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58919, first published .
Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study

Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study

Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study

Authors of this article:

Shuo-Yu Lin1 Author Orcid Image ;   Sahithi Kiran Tulabandu2 Author Orcid Image ;   J Randy Koch3 Author Orcid Image ;   Rashelle Hayes4 Author Orcid Image ;   Andrew Barnes5 Author Orcid Image ;   Hemant Purohit6 Author Orcid Image ;   Songqing Chen7 Author Orcid Image ;   Bo Han7 Author Orcid Image ;   Hong Xue1 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Ji T, Liu Z, Su Z, Xia X, Liu Y, Xie Y, Huang Z, Zhou X, Wang M, Cheng A, Song Q, Shi Y, Shi S, Ailifeire A, He J, Gao Y, Zhao L, Wu L, Xiao D, Wang C. E-Cigarette Narratives of User-Generated Posts on Xiaohongshu in China: Content Analysis (Preprint). Journal of Medical Internet Research 2025 View
  2. Olawade D, Aienobe-Asekharen C. Artificial intelligence in tobacco control: A systematic scoping review of applications, challenges, and ethical implications. International Journal of Medical Informatics 2025;202:105987 View