Titre:	Predictive model for Brazilian presidential election based on analysis of social media
Auteur(s):	Silva, Guilherme Costa, Mirele Drummond, André Li Weigang
Assunto::	Previsão Eleições - Brasil Teorema de Bayes Mídia social
Date de publication:	2019
Editeur:	Springer
Référence bibliographique:	SILVA, 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.
Abstract:	The 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.
metadata.dc.description.unidade:	Instituto de Ciências Exatas (IE) Departamento de Ciência da Computação (IE CIC)
metadata.dc.relation.publisherversion:	https://link.springer.com/chapter/10.1007/978-3-030-32591-6_5
Collection(s) :	Trabalhos apresentados em evento

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