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Resumo  Este artigo se propoe a ampliar a metodologia perspectivista (MALINI, 2016) de analise de redes sociais, incorporando um procedimento de analise dos sentimentos das mensagens postadas em redes de controversias politicas, em particular, em dois momentos distintos da campanha pelo impeachment da presidenta Dilma. O primeiro e o periodo da eclosao das manifestacoes antipetistas, no dia 15 de marco de 2015. O segundo, dia 27 de agosto de 2016, quando a presidenta e deposta do cargo. Realiza uma revisao sobre a analise de sentimentos em megadados do Twitter e constroi uma metodologia que combina classificacao humana de textos com aplicacao de algoritmos geneticos de analise de textos, no intuito de analisar sentimentos genericos (baseado na polarizacao positivo/negativos) e sentimento especificos, baseados nas seguintes emocoes: Alegria, Raiva, Medo, Antecipacao, Desgosto, Tristeza, Surpresa e Confianca. Conclui demonstrando que os movimentos pro e anti-Dilma sao marcados pelo predominio de sentimento de raiva, medo e ansiedade, confirmando a hipotese que a trolagem ofensiva demarca o estilo da indignacao propagada em redes politicas no Twitter brasileiro.   Palavras-Chave : Analise de Sentimento; Big Data; Redes; Politica; Twitter. Abstract  This article aims to expand the perspectivist methodology (Malini, 2016) of social networks analysis, incorporating a proceeding of sentiment analysis of the messages posted in networks of political controversies, in particular, in two distinct moments of the campaign for the impeachment of President Dilma. The first is the period of the outbreak of PT protests, on March 15, 2015. The second, on August 27, 2016, when the president is deposed. We will be doing a theoretical review about sentiment analysis in Big Data on Twitter to build a methodology that combines human classification of texts with the application of genetic algorithms of text analysis and to analyze generic sentiments (based on positive / negative polarization) and specific sentiment, based on emotions like Joy, Anger, Fear, Anticipation, Disgust, Sadness, Surprise and Trust. It concludes by demonstrating that pro and anti-Dilma movements are marked by a predominance of anger, fear and anxiety, confirming the hypothesis that an offensive trolling demarcates the style of indignation propagated by political networks in Brazilian Twitter. Keywords : Sentiment Analysis; Big Data; Social Network; Politics; Twitter.

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O sentimento político em redes sociais: big data, algoritmos e as emoções nos tweets sobre o impeachment de Dilma Rousseff | Political sentiment in social networks: big data, algorithims and emotions in tweets about the impeachment of Dilma Rousseff