Um modelo para predição de bolsa de valores baseado em mineração de opinião

• Ano de defesa: 2016
• Autor(a) principal: Lima, Milson Louseiro
• Orientador(a): LABIDI, Sofiane
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Maranhão
• Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
• Departamento: Engenharia
• País: BR
• Palavras-chave em Português: Mineração de Opinião; Análise de Sentimento; Twitter; Bolsa de Valores; Inteligência Artificial.
• Palavras-chave em Inglês: Opinion mining; Sentiment Analysis; Twitter; Stock Market; Artificial intelligence
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://tedebc.ufma.br:8080/jspui/handle/tede/297

Predicting the behavior of stocks in the stock market is a challenging task, a lot of times related to unknown factors or influenced by very distinct natures of variables, which can range from high-profile news to the collective sentiment, expressed in publications on social networks. Such market volatility may represent considerable financial losses for investors. In order to forestall such variations other mechanisms to predict the behavior of assets in the stock market have been proposed, based on pre-existing indicator data. Such mechanisms only analyze statistical data, not considering the collective human sentiment. This work aims to develop a model to predict the stock market, based on analysis of sentiment and it will make use of techniques of artificial intelligence as natural language processing (PLN) and Support Vector Machines (SVM) to predict the active behavior. However, it should be emphasized that this model is intended to be an aid tool in the decision-making process that involves buying and selling shares on the stock market.