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

Infodemiology and Infoveillance (1456) Behavioural Surveillance for Public Health (253) Substance and Alcohol Abuse in Adolescence (121) Artificial Intelligence (1740) Social Media in Adolescence (57) Smoking and Vaping in Adolescence (33) Natural Language Processing (801)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55591, first published .
The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study

The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study

The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study

Authors of this article:

Sungwon Jung1 Author Orcid Image ;   Dhiraj Murthy1 Author Orcid Image ;   Bara S Bateineh2 Author Orcid Image ;   Alexandra Loukas3 Author Orcid Image ;   Anna V Wilkinson2 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Murthy D, Keshari S, Arora S, Yang Q, Loukas A, Schwartz S, Harrell M, Hébert E, Wilkinson A. Categorizing E-cigarette-related tweets using BERT topic modeling. Emerging Trends in Drugs, Addictions, and Health 2024;4:100160 View
  2. Vassey J, Kennedy C, Chang H, Unger J. Generative AI in a new era of computer model-informed tobacco research: a short report. Tobacco Control 2025:tc-2024-058887 View
  3. Biles J, Kornhaber R, Irwin P, Schineanu A, Kavisha Sookraj-Baran M, Cleary M. Perspectives, motivations, and experiences of adolescents and young adults using nicotine vapes: a qualitative review. Health Promotion International 2025;40(2) View
  4. Bataineh B, Marti C, Murthy D, Badillo D, Chow S, Loukas A, Wilkinson A. Vaping, Acculturation, and Social Media Use Among Mexican American College Students: Protocol for a Mixed Methods Web-Based Cohort Study. JMIR Research Protocols 2025;14:e63584 View