Tweet
Health Inf Sci Syst. 2015 Feb 24;3(Suppl 1 HISA Big Data in Biomedicine and Healthcare 2013 Con):S4. doi: 10.1186/2047-2501-3-S1-S4. eCollection 2015.
Automatic detection of tweets reporting cases of influenza like illnesses in Australia.
Zuccon G1, Khanna S2, Nguyen A2, Boyle J2, Hamlet M2, Cameron M3.
Author information
Abstract
Early detection of disease outbreaks is critical for disease spread control and management. In this work we investigate the suitability of statistical machine learning approaches to automatically detect Twitter messages (tweets) that are likely to report cases of possible influenza like illnesses (ILI). Empirical results obtained on a large set of tweets originating from the state of Victoria, Australia, in a 3.5 month period show evidence that machine learning classifiers are effective in identifying tweets that mention possible cases of ILI (up to 0.736 F-measure, i.e. the harmonic mean of precision and recall), regardless of the specific technique implemented by the classifier investigated in the study.
PMID: 25870759 [PubMed]
Automatic detection of tweets reporting cases of influenza like illnesses in Australia.
Zuccon G1, Khanna S2, Nguyen A2, Boyle J2, Hamlet M2, Cameron M3.
Author information
Abstract
Early detection of disease outbreaks is critical for disease spread control and management. In this work we investigate the suitability of statistical machine learning approaches to automatically detect Twitter messages (tweets) that are likely to report cases of possible influenza like illnesses (ILI). Empirical results obtained on a large set of tweets originating from the state of Victoria, Australia, in a 3.5 month period show evidence that machine learning classifiers are effective in identifying tweets that mention possible cases of ILI (up to 0.736 F-measure, i.e. the harmonic mean of precision and recall), regardless of the specific technique implemented by the classifier investigated in the study.
PMID: 25870759 [PubMed]