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Tweet Sentiment Analysis Regarding The Brazilian Stock Market

Murilo C. Medeiros, Vinicius R. P. Borges

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This paper describes a methodology for analyzing sentiments and for knowledge discovery in tweets regarding the Brazilian stock market. The proposed methodology starts by preprocessing and characterizing tweets to obtain an associated vector-space model. After that, a dimensionality reduction is em- ployed by using Principal Component Analysis and t-Stochastic Neighbor Embedding. Sentiment analysis of stock market tweets is performed by considering the tasks of sentiment classification, topic modeling and clustering, along with a visual analysis process. Experiments results showed satisfactory performances in single and multi-label sentiment classification scenarios. The visual analysis process also revealed interesting relationships among topics and clusters.