Author :
Milson L. Lima
Affiliation : Federal University of Maranhão
Country : Brazil
Category : Computer Science & Information Technology
Volume, Issue,
Month, Year
: 6, 1, November, 2016
ABSTRACT
Predicting
the behavior of shares in the stock market is a complex problem, that involves
variables not always known and can undergo various influences, from the
collective emotion to high-profile news. Such volatility, can represent
considerable financial losses for investors. In order to anticipate such
changes in the market, it has been proposed various mechanisms to try to
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. This article, is going to use natural
language processing algorithms (LPN) to determine the collective mood on assets
and later with the help of the SVM algorithm to extract patterns in an attempt
to predict the active behavior. Nevertheless it is important to note that such
approach is not intended to be the main factor in the decision making process,
but rather an aid tool, which combined with other information, can provide
higher accuracy for the solution of this problem.
Keyword : Sentiment Analysis, Twitter, Prediction of
Stock Exchanges
For More Details : https://airccj.org/CSCP/vol6/csit64812.pdf
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