Influenza-Like Illness Surveillance on Twitter through Automated Learning of Naïve Language

Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algor...

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Bibliographische Detailangaben
Hauptverfasser: Gesualdo, Francesco, Stilo, Giovanni, Agricola, Eleonora, Gonfiantini, Michaela V., Pandolfi, Elisabetta, Velardi, Paola, Tozzi, Alberto E.
Format: Artigo
Sprache:Inglês
Veröffentlicht: Public Library of Science 2013
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Research Article
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC3853203/
https://ncbi.nlm.nih.gov/pubmed/24324799
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0082489
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