For or Against?: Polarity Analysis in Tweets about Impeachment Process of Brazil President - Souza, Bruno A.; Almeida, Thais G.; Menezes, Alice A. F.; Nakamura, Fabíola Guerra; Figueiredo, Carlos Mauricio S.; Nakamura, Eduardo Freire (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia), 2016)
Social networks define a major media for users to express their opinion regarding different matters. As a consequence, these networks naturally provide information that allow us to detect user behaviors, opinions, and sentiments about diverse events around the world. One event that called attention in Brazil is the impeachment process of the Brazillian President. The goal of this paper is to infer and characterize the opinion (polarity) of the Brazilians about the impeachment process in Brazil. We used a supervised learning approach and compared three classifiers: Max Entropy, Support Vector Machine (SVM), and Multinomial Naive Bayes. The SVM presented the best performance for detecting the comments’ polarity about the impeachment process. In some cases, the SVM presented an F-score at least 1.03% higher than the others.