Using social connection information to improve opinion mining: Identifying negative sentiment about HPV vaccines on Twitter

Studies in Health Technology and Informatics

Volumn 216, Issue , 2015, Pages 761-765

  Zhou, Xujuan ^a   Coiera, Enrico ^a   Tsafnat, Guy ^a   Arachi, Diana ^a   Ong, Mei Sing ^a,b   Dunn, Adam G ^a  

^a MACQUARIE UNIVERSITY   (Australia)

^b BOSTON CHILDREN S HOSPITAL   (United States)

Author keywords

HPV vaccines; Machine learning; Public health surveillance; Social media; Text mining; Twitter messaging

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; CLASSIFICATION (OF INFORMATION); EPIDEMIOLOGY; LEARNING SYSTEMS; MONITORING; PUBLIC HEALTH; SENTIMENT ANALYSIS; SOCIAL NETWORKING (ONLINE); STATISTICAL TESTS; TEXT MESSAGING; VACCINES;

CONTENT-BASED CLASSIFIERS; HUMAN PAPILLOMAVIRUS; MACHINE LEARNING METHODS; NEGATIVE SENTIMENTS; PUBLIC HEALTH SURVEILLANCES; SOCIAL MEDIA; TEXT MINING; TWITTER MESSAGING;

DATA MINING;

WART VIRUS VACCINE;

ATTITUDE TO HEALTH; DATA MINING; NATURAL LANGUAGE PROCESSING; PROCEDURES; PSYCHOLOGY; PUBLIC OPINION; SOCIAL MEDIA; SOCIAL SUPPORT; STATISTICS AND NUMERICAL DATA; VACCINATION;

ATTITUDE TO HEALTH; DATA MINING; NATURAL LANGUAGE PROCESSING; PAPILLOMAVIRUS VACCINES; PUBLIC OPINION; SOCIAL MEDIA; SOCIAL SUPPORT; VACCINATION;

EID: 84952034317     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: 10.3233/978-1-61499-564-7-761     Document Type: Conference Paper

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