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Volumn , Issue , 2013, Pages 699-702

Validating models for disease detection using twitter

Author keywords

Data mining; Machine learning; Regression; Twitter

Indexed keywords

ARTIFICIAL INTELLIGENCE; DISEASES; LEARNING SYSTEMS; SOCIAL NETWORKING (ONLINE);

EID: 84891758338     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2487788.2488027     Document Type: Conference Paper
Times cited : (53)

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    • Culotta, A.1
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    • Take two aspirin and tweet me in the morning: How twitter, facebook, and other social media are reshaping health care
    • C. Hawn. Take two aspirin and tweet me in the morning: how Twitter, Facebook, and other social media are reshaping health care. Health Affairs, 2009.
    • (2009) Health Affairs
    • Hawn, C.1
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    • Assessing vaccination sentiments with online social media: Implications for infectious disease dynamics and control
    • Oct
    • M. Salathé and S. Khandelwal. Assessing vaccination sentiments with online social media: implications for infectious disease dynamics and control. PLoS computational biology, 7(10):e1002199, Oct. 2011.
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    • Salathé, M.1    Khandelwal, S.2
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    • The use of twitter to track levels of disease activity and public concern in the u.s. During the inuenza a h1n1 pandemic
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    • Can twitter predict disease outbreaks?
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    • R: A language and environment for statistical computing
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.