Modeling spatiotemporal factors associated with sentiment on twitter: Synthesis and suggestions for improving the identification of localized deviations

Journal of Medical Internet Research

Volumn 21, Issue 5, 2019, Pages

  Shah, Zubair ^a   Martin, Paige ^a   Coiera, Enrico ^a   Mandl, Kenneth D ^b,c   Dunn, Adam G ^a  

^a MACQUARIE UNIVERSITY   (Australia)

^b BOSTON CHILDREN S HOSPITAL   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Public health; Social media; Text mining

Indexed keywords

ARTICLE; CITY; CONVERSATION; ENGLISH (LANGUAGE); HUMAN; HUMAN EXPERIMENT; MINING; PUBLIC HEALTH; SOCIAL MEDIA; SYNTHESIS; TELECOMMUNICATION; WEATHER; SPATIOTEMPORAL ANALYSIS;

HUMANS; SOCIAL MEDIA; SPATIO-TEMPORAL ANALYSIS;

EID: 85067226078     PISSN: None     EISSN: 14388871     Source Type: Journal    
DOI: 10.2196/12881     Document Type: Article

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