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

Infoveillance and Social Listening (244) Infodemiology and Infoveillance (1448) Smoking Cessation (590)

Published on in Vol 2, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37412, first published .
Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series

Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series

Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series

Authors of this article:

Nnamdi C Ezike1 Author Orcid Image ;   Allison Ames Boykin1 Author Orcid Image ;   Page D Dobbs1 Author Orcid Image ;   Huy Mai2 Author Orcid Image ;   Brian A Primack3 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Ranker L, Tofu D, Lu M, Wu J, Bhatnagar A, Robertson R, Wijaya D, Hong T, Fetterman J, Xuan Z. Concurrent Mentions of Vaping and Alcohol on Twitter: Latent Dirichlet Analysis. Journal of Medical Internet Research 2024;26:e51870 View
  2. Calac A, McMann T, Li Z, Cuomo R, Mackey T. Representation of commercial and traditional tobacco on social media: deconstructing historical narratives to address the Indigenous youth tobacco epidemic. Tobacco Control 2025:tc-2024-058881 View