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)

Published on in Vol 20, No 8 (2018): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9373, first published .
Understanding Users’ Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques

Understanding Users’ Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques

Understanding Users’ Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques

Authors of this article:

Qiudan Li1 Author Orcid Image ;   Can Wang1, 2 Author Orcid Image ;   Ruoran Liu1, 2 Author Orcid Image ;   Lei Wang1 Author Orcid Image ;   Daniel Dajun Zeng1, 2, 3 Author Orcid Image ;   Scott James Leischow4 Author Orcid Image
Article Authors Cited by (8) Tweetations (9) Metrics

Journals

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  2. Lu X, Chen L, Yuan J, Luo J, Luo J, Xie Z, Li D. User Perceptions of Different Electronic Cigarette Flavors on Social Media: Observational Study. Journal of Medical Internet Research 2020;22(6):e17280 View
  3. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  4. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660 View
  5. Trucco E, Fallah-Sohy N, Hartmann S, Cristello J. Electronic Cigarette Use Among Youth: Understanding Unique Risks in a Vulnerable Population. Current Addiction Reports 2020;7(4):497 View
  6. Hswen Y, Yom-Tov E. Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data. International Journal of Environmental Research and Public Health 2021;18(15):8203 View
  7. He L, Yin T, Zheng K. They May Not Work! An evaluation of eleven sentiment analysis tools on seven social media datasets. Journal of Biomedical Informatics 2022;132:104142 View
  8. Ungless E, Ross B, Belle V. Potential Pitfalls With Automatic Sentiment Analysis: The Example of Queerphobic Bias. Social Science Computer Review 2023;41(6):2211 View