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Mining Social Media Data for Biomedical Signals and Health-Related Behavior

Authors
  • Correia, Rion Brattig
  • Wood, Ian B.
  • Bollen, Johan
  • Rocha, Luis M.
Type
Published Article
Journal
Annual Review of Biomedical Data Science
Publisher
Annual Reviews
Publication Date
Jul 20, 2020
Volume
3
Pages
433–458
Identifiers
DOI: 10.1146/annurev-biodatasci-030320-040844
Source
Annual Reviews
Keywords
License
Yellow

Abstract

Social media data have been increasingly used to study biomedical and health-related phenomena. From cohort-level discussions of a condition to population-level analyses of sentiment, social media have provided scientists with unprecedented amounts of data to study human behavior associated with a variety of health conditions and medical treatments. Here we review recent work in mining social media for biomedical, epidemiological, and social phenomena information relevant to the multilevel complexity of human health. We pay particular attention to topics where social media data analysis has shown the most progress, including pharmacovigilance and sentiment analysis, especially for mental health. We also discuss a variety of innovative uses of social media data for health-related applications as well as important limitations of social media data access and use.

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