Content Analysis of Tobacco-related Twitter Posts

Authors

  • Mark Myslín University of California, San Diego
  • Shu-Hong Zhu University of California, San Diego
  • Michael Conway University of California, San Diego

DOI:

https://doi.org/10.5210/ojphi.v5i1.4603

Abstract

Results of a content analysis of tobacco-related Twitter posts (tweets), with particular reference to e-cigarette and hookah related tweets. Descriptive results reveal more positive than negative sentiment toward tobacco among Twitter uses, as well as several apparent disconnects between public perception and tobacco-related health research, presenting opportunities for improved outreach and education. Additionally, machine classification of tobacco-related posts shows a promising edge over strictly keyword-based approaches, paving the way for automated tobacco surveillance applications.

Author Biography

Mark Myslín, University of California, San Diego

Mark Myslín is a PhD student in Linguistics and Cognitive Science at UCSD, where he is a member of the Computational Psycholinguistics Lab. His interests lie at the intersection of cognitive psychology, computational linguistics, and conversational discourse and interaction.

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Published

2013-03-24

How to Cite

Myslín, M., Zhu, S.-H., & Conway, M. (2013). Content Analysis of Tobacco-related Twitter Posts. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4603

Issue

Section

Oral Presentations: Social and News Media