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dc.contributor.authorLazer, David M.
dc.contributor.authorKennedy, R.
dc.contributor.authorKing, Gary
dc.contributor.authorVespignani, A.
dc.date.accessioned2014-03-28T20:32:37Z
dc.date.issued2014
dc.identifier.citationLazer, D., R. Kennedy, G. King, and A. Vespignani. 2014. “The Parable of Google Flu: Traps in Big Data Analysis.” Science 343 (6176) (March 14): 1203–1205.en_US
dc.identifier.issn0193-4511en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12016836
dc.description.abstractLarge errors in flu prediction were largely avoidable, which offers lessons for the use of big data. In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States ( 1, 2). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data ( 3, 4), what lessons can we draw from this error?en_US
dc.description.sponsorshipOther Research Uniten_US
dc.language.isoen_USen_US
dc.publisherAmerican Association for the Advancement of Science (AAAS)en_US
dc.relation.isversionofdoi:10.1126/science.1248506en_US
dc.relation.hasversionhttp://gking.harvard.edu/publications/parable-google-flu%C2%A0traps-big-data-analysisen_US
dash.licenseOAP
dc.titleThe Parable of Google Flu: Traps in Big Data Analysisen_US
dc.typeJournal Articleen_US
dc.description.versionAccepted Manuscripten_US
dc.relation.journalScienceen_US
dash.depositing.authorKing, Gary
dc.date.available2014-03-28T20:32:37Z
dc.data.urihttp://dx.doi.org/10.7910/DVN/24823en_US
dc.identifier.doi10.1126/science.1248506*
dash.identifier.orcid0000-0002-5327-7631*
dash.contributor.affiliatedLazer, David
dash.contributor.affiliatedKing, Gary
dc.identifier.orcid0000-0002-5327-7631


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