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

Early Results in Infodemiology and Infoveillance (115) Infodemiology and Infoveillance (1613) Public (e)Health, Digital Epidemiology and Public Health Informatics (1142) Mass Media/Social Media Communication and Campaigns (612) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1170) Behavioural Surveillance for Public Health (321) Attitudes, Beliefs, and Health Behaviours in Human Factors Research (100)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63035, first published .
Public Perceptions of Very Low Nicotine Content on Twitter: Observational Study

Public Perceptions of Very Low Nicotine Content on Twitter: Observational Study

Public Perceptions of Very Low Nicotine Content on Twitter: Observational Study

Authors of this article:

Zidian Xie1 Author Orcid Image ;   Xinyi Liu2 Author Orcid Image ;   Xubin Lou2 Author Orcid Image ;   Dongmei Li1 Author Orcid Image
Article Authors Cited by (1) Tweetations (7) Metrics

Journals

  1. Xie Z, Ye P, Wu M, Han Y, Shimazaki Y, Ross J, Sutfin E, Li D. Understanding online sentiment toward waterpipe tobacco smoking by applying deep-learning language models to Twitter posts (2021–2023) in the United States. Nicotine & Tobacco Research 2026 View