2020/01/28 by Rion Brattig Correia, Ian B. Wood, Johan Bollen +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Pharmacology, Toxicology and Pharmaceutics · Psychology · #Mental Health via Writing #Pharmacovigilance and Adverse Drug Reactions #Sentiment Analysis and Opinion Mining #cs.CY #cs.SI #q-bio.QM
paper · pdf · doi:10.1146/annurev-biodatasci-030320-040844
published as Annual Review of Biomedical Data Science, 3:1 (2020) · To appear in the Annual Review of Biomedical Data Science
arxiv created 2020/01/28 · openalex created_date 2020/02/07 · openalex publication_date 2020/05/04 · arxiv updated 2020/09/17 · openalex updated_date 2026/08/04
Social media data has been increasingly used to study biomedical and health-related phenomena. From cohort level discussions of a condition to planetary level analyses of sentiment, social media has provided scientists with unprecedented amounts of data to study human behavior and response 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, sentiment analysis especially for mental health, and other areas. We also discuss a variety of innovative uses of social media data for health-related applications and important limitations in social media data access and use.