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dc.contributor.authorSilva, Guilherme-
dc.contributor.authorCosta, Mirele-
dc.contributor.authorDrummond, André-
dc.contributor.authorLi Weigang-
dc.date.accessioned2020-03-05T11:51:27Z-
dc.date.available2020-03-05T11:51:27Z-
dc.date.issued2019-
dc.identifier.citationSILVA, Guilherme et al. Predictive model for Brazilian presidential election based on analysis of social media. In: INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, 15., 2019, Kunming.pt_BR
dc.identifier.urihttps://repositorio.unb.br/handle/10482/37047-
dc.language.isoInglêspt_BR
dc.publisherSpringerpt_BR
dc.rightsAcesso Restritopt_BR
dc.titlePredictive model for Brazilian presidential election based on analysis of social mediapt_BR
dc.typeTrabalhopt_BR
dc.subject.keywordPrevisãopt_BR
dc.subject.keywordEleições - Brasilpt_BR
dc.subject.keywordTeorema de Bayespt_BR
dc.subject.keywordMídia socialpt_BR
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-030-32591-6_5pt_BR
dc.description.abstract1The prediction of presidential election outcome is key point of interest for politicians, electors and sponsoring companies. The 2018 Brazilian election presented a scenario with many uncertainties increasing prediction challenge. The utilization of social media as the promotion tools is another new scenario for both election and also prediction. In this paper, we present a Bayesian forecasting model based on the data from public opinion polls to predict the votes of undecided voters, about a third of the population. The migration of votes among candidates during the electoral period was also analyzed. By using the data from social media in the decision-making process, the proposed model and application show the capability to estimate the voting numbers of the main candidates with better accuracy than public opinion polls.pt_BR
dc.description.unidadeInstituto de Ciências Exatas (IE)-
dc.description.unidadeDepartamento de Ciência da Computação (IE CIC)-
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