Sentiment analysis of the 2018 brazilian elections using Twitter - Franco, Rafael Bilibio; Adaniya, Mario Henrique Akihiko da Costa (Revista Terra & Cultura: Cadernos de Ensino e Pesquisa; Vol 39 No 76 (2023): Publicação Contínua, 2023)
The rise of social networks has profoundly changed the way information and opinions are propagated, providing an unprecedented amount of data. This has, however, brought new problems. Extracting relevant and assertive information from such a tangle of data is one of the greatest and most rewarding contemporary challenges. Sentiment analysis lends itself to solving this problem. In it, computational techniques are employed with the objective of building systems that act in an automated way in the classification of feelings extracted from documents written in natural language, such as those coming from social networks. In this work, the main concepts, standards and techniques used in sentiment analysis are gathered, with a special focus on the works that have been developed for the prediction of government elections using data from Twitter. After reviewing the fundamental themes underlying the studies in this area, an experiment was described that used sentiment analysis to measure the rejection of the three main candidates for the Brazilian presidential elections of 2018, in order to compare the results obtained here with those of traditional methodologies of research, represented here by the electoral surveys of the Datafolha Institute.