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How (not) to predict elections

dc.contributor.authorMetaxas, Panagiotis T.spa
dc.contributor.authorMustafaraj, Enispa
dc.contributor.authorGayo Avello, Daniel spa
dc.date.accessioned2013-01-30T12:38:55Z
dc.date.available2013-01-30T12:38:55Z
dc.date.issued2011spa
dc.identifier.isbn978-1-4577-1931-8spa
dc.identifier.urihttp://hdl.handle.net/10651/12386
dc.description2011 IEEE International Conference on Privacy, Security, Risk, and Trust, and IEEE International Conference on Social Computing, Bostonspa
dc.description.abstractUsing social media for political discourse is increasingly becoming common practice, especially around election time. Arguably, one of the most interesting aspects of this trend is the possibility of ''pulsing'' the public's opinion in near real-time and, thus, it has attracted the interest of many researchers as well as news organizations. Recently, it has been reported that predicting electoral outcomes from social media data is feasible, in fact it is quite simple to compute. Positive results have been reported in a few occasions, but without an analysis on what principle enables them. This, however, should be surprising given the significant differences in the demographics between likely voters and users of online social networks. This work aims to test the predictive power of social media metrics against several Senate races of the two recent US Congressional elections. We review the findings of other researchers and we try to duplicate their findings both in terms of data volume and sentiment analysis. Our research aim is to shed light on why predictions of electoral (or other social events) using social media might or might not be feasible. In this paper, we offer two conclusions and a proposal: First, we find that electoral predictions using the published research methods on Twitter data are not better than chance. Second, we reveal some major challenges that limit the predictability of election results through data from social media. We propose a set of standards that any theory aiming to predict elections (or other social events) using social media should follow.en
dc.format.extentp. 165-171spa
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofPASSAT/SocialCom 2011. 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computingspa
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/es/
dc.subjectElectionsen
dc.subjectPredictionen
dc.subjectSocial Media Analysisen
dc.subjectTwitteren
dc.titleHow (not) to predict electionseng
dc.typeinfo:eu-repo/semantics/conferenceObjectspa
dc.identifier.doi10.1109/PASSAT/SocialCom.2011.98spa
dc.type.dcmitextspa
dc.relation.publisherversionhttp://dx.doi.org/10.1109/PASSAT/SocialCom.2011.98


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CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
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