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

Machine Learning (1505) Infodemiology and Infoveillance (1369) Advanced Data Analytics in eHealth (142) Big Data (246) Discourse (38)

Published on in Vol 10, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33678, first published .
Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study

Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study

Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study

Authors of this article:

William Baker1 Author Orcid Image ;   Jason B Colditz2 Author Orcid Image ;   Page D Dobbs3 Author Orcid Image ;   Huy Mai1 Author Orcid Image ;   Shyam Visweswaran4 Author Orcid Image ;   Justin Zhan1 Author Orcid Image ;   Brian A Primack5 Author Orcid Image
Article Authors Cited by (11) Tweetations (5) Metrics

Journals

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  2. Dobbs P, Boykin A, Ezike N, Myers A, Colditz J, Primack B. Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis. JMIR Formative Research 2023;7:e50346 View
  3. Tian Y, Zhang W, Duan L, McDonald W, Osgood N. Comparison of pretrained transformer-based models for influenza and COVID-19 detection using social media text data in Saskatchewan, Canada. Frontiers in Digital Health 2023;5 View
  4. Kar A, Varsha P, Rajan S. Unravelling the Impact of Generative Artificial Intelligence (GAI) in Industrial Applications: A Review of Scientific and Grey Literature. Global Journal of Flexible Systems Management 2023;24(4):659 View
  5. Lee J, Ouellette R, Murthy D, Pretzer B, Anand T, Kong G. Identifying E-cigarette Content on TikTok: Using a BERTopic Modeling Approach. Nicotine and Tobacco Research 2024 View
  6. 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
  7. de Anta L, Alvarez-Mon M, Pereira-Sanchez V, Donat-Vargas C, Lara-Abelenda F, Arrieta M, Montero-Torres M, García-Montero C, Fraile-Martínez Ó, Mora F, Ortega M, Alvarez-Mon M, Quintero J. Assessment of beliefs and attitudes towards benzodiazepines using machine learning based on social media posts: an observational study. BMC Psychiatry 2024;24(1) View
  8. He L. Enhanced twitter sentiment analysis with dual joint classifier integrating RoBERTa and BERT architectures. Frontiers in Physics 2024;12 View