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Don't turn social media into another 'literary digest' poll

dc.contributor.authorGayo Avello, Daniel 
dc.date.accessioned2013-01-30T10:24:38Z
dc.date.available2013-01-30T10:24:38Z
dc.date.issued2011
dc.identifier.citationCommunications of the ACM, 54(10), p. 121-128 (2011); doi:10.1145/2001269.2001297spa
dc.identifier.issn0001-0782
dc.identifier.urihttp://hdl.handle.net/10651/11452
dc.description.abstractUser generated content has experienced an explosive growth both in the diversity of applications and the volume of topics covered by its users. Content published in micro-blogging systems like Twitter is thought to be feasibly data-mined in order to take the pulse of society. Recently, a number of positive studies have been published praising the goodness of relatively simple approaches to sampling, opinion mining, and sentiment analysis. This paper will attempt to play devil's advocate by detailing a study in which such simple approaches largely overestimated Obama's victory in the 2008 U.S. Presidential Elections. A thorough post-mortem of that experiment has been conducted and several important lessons have been extracte
dc.format.extentp. 121-128spa
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofCommunications of the ACM, 54(10)spa
dc.rights© ACM, 2011
dc.titleDon't turn social media into another 'literary digest' pollspa
dc.typeinfo:eu-repo/semantics/article
dc.identifier.local20110941spa
dc.identifier.doi10.1145/2001269.2001297
dc.type.dcmitextspa
dc.relation.publisherversionhttp://dx.doi.org/10.1145/2001269.2001297


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