出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Predicting the behavior of shares in the stock market is a complex problem, that involvesvariables not always known and can undergo various influences, from the collective emotion tohigh-profile news. Such volatility, can represent considerable financial losses for investors. Inorder to anticipate such changes in the market, it has been proposed various mechanisms to tryto predict the behavior of an asset in the stock market, based on previously existing information.Such mechanisms include statistical data only, without considering the collective feeling. Thisarticle, is going to use natural language processing algorithms (LPN) to determine thecollective mood on assets and later with the help of the SVM algorithm to extract patterns in anattempt to predict the active behavior. Nevertheless it is important to note that such approach isnot intended to be the main factor in the decision making process, but rather an aid tool, whichcombined with other information, can provide higher accuracy for the solution of this problem.
关键词：Sentiment Analysis; Twitter; Prediction of Stock Exchanges
