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Limits of Electoral Predictions using Twitter

dc.contributor.authorGayo Avello, Daniel spa
dc.contributor.authorMetaxas, Panagiotis T.spa
dc.contributor.authorMustafaraj, Enispa
dc.date.accessioned2013-01-30T12:36:09Z
dc.date.available2013-01-30T12:36:09Z
dc.date.issued2011spa
dc.identifier.isbn978-1-57735-505-2spa
dc.identifier.urihttp://hdl.handle.net/10651/11899
dc.identifier.urihttp://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2862
dc.descriptionFifth International AAAI Conference on Weblogs and Social, 17-21 July 2011, Barcelona, Spainspa
dc.description.abstractUsing social media for political discourse is becoming common practice, especially around election time. One interesting aspect of this trend is the possibility of pulsing the public’s opinion about the elections, and that has attracted the interest of many researchers and the press. Allegedly, predicting electoral outcomes from social media data can be feasible and even simple. Positive results have been reported, but without an analysis on what principle enables them. Our work puts to test the purported predictive power of social media metrics against the 2010 US congressional elections. Here, we applied techniques that had reportedly led to positive election predictions in the past, on the Twitter data collected from the 2010 US congressional elections. Unfortunately, we find no correlation between the analysis results and the electoral outcomes, contradicting previous reports. Observing that 80 years of polling research would support our findings, we argue that one should not be accepting predictions about events using social media data as a black box. Instead, scholarly research should be accompanied by a model explaining the predictive power of social media, when there is one.spa
dc.format.extentp. 490-493spa
dc.language.isoeng
dc.publisherAssociation for the Advancement of Artificial Intelligence
dc.relation.ispartofProceedings of the Fifth International AAAI Conference on Weblogs and Social Media
dc.rights© Association for the Advancement of Artificial Intelligencespa
dc.titleLimits of Electoral Predictions using Twitterspa
dc.typeinfo:eu-repo/semantics/conferenceObjectspa
dc.type.dcmitextspa


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