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

Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Smoking Cessation (557) Mass Media/Social Media Communication and Campaigns (461)

Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25579, first published .
Topics of Nicotine-Related Discussions on Twitter: Infoveillance Study

Topics of Nicotine-Related Discussions on Twitter: Infoveillance Study

Topics of Nicotine-Related Discussions on Twitter: Infoveillance Study

Authors of this article:

Jon-Patrick Allem1 Author Orcid Image ;   Allison Dormanesh1 Author Orcid Image ;   Anuja Majmundar2 Author Orcid Image ;   Jennifer B Unger1 Author Orcid Image ;   Matthew G Kirkpatrick1 Author Orcid Image ;   Akshat Choube3 Author Orcid Image ;   Aneesh Aithal3 Author Orcid Image ;   Emilio Ferrara3 Author Orcid Image ;   Tess Boley Cruz1 Author Orcid Image
Article Authors Cited by (9) Tweetations (12) Metrics

Journals

  1. Purushothaman V, McMann T, Li Z, Cuomo R, Mackey T. Content and trend analysis of user-generated nicotine sickness tweets: A retrospective infoveillance study. Tobacco Induced Diseases 2022;20(March):1 View
  2. Chan L, Harris-Roxas B, Freeman B, MacKenzie R, Woodland L, O'Hara B. Attitudes towards the ‘Shisha No Thanks’ campaign video: Content analysis of Facebook comments. Tobacco Induced Diseases 2022;20(October):1 View
  3. Silver N, Kierstead E, Briggs J, Schillo B. Charming e-cigarette users with distorted science: a survey examining social media platform use, nicotine-related misinformation and attitudes towards the tobacco industry. BMJ Open 2022;12(6):e057027 View
  4. Allem J, Donaldson S, Vogel E, Pang R, Unger J. An Analysis of Twitter Posts About the U.S. Food and Drug Administration’s Menthol Ban. Nicotine & Tobacco Research 2022 View
  5. Chu A, Chong A, Lai N, Tiwari A, So M. Enhancing the Predictive Power of Google Trends Data Through Network Analysis: Infodemiology Study of COVID-19. JMIR Public Health and Surveillance 2023;9:e42446 View
  6. Galimov A, Kirkpatrick M, Vassey J, Galstyan E, Smith A, Allem J, Unger J. Oral Nicotine Gum Discussions on Twitter: Content Analysis. Nicotine and Tobacco Research 2024;26(4):503 View
  7. Slavin S, Berman A, Beam A, Navar A, Mittleman M. Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022. Journal of the American Heart Association 2024;13(7) View
  8. Wu D, Shead H, Ren Y, Raynor P, Tao Y, Villanueva H, Hung P, Li X, Brookshire R, Eichelberger K, Guille C, Litwin A, Olatosi B. Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e53171 View
  9. Han E, Biyani M, Hrywna M, Donaldson S, Allem J. Identifying Topics Around Nicotine Gum: A Machine Learning Approach with Twitter Data. Substance Use & Misuse 2024:1 View