Stock Market Prediction Based on News Sentiments

Abstract

Abstract

In today’s era, the count of investor is increasing day by day. For identifying the market risk and for the growth of profit, the market stock prediction is an important factor. People are using traditional theorems for predicting market behavior. Different methods are used for predicting the market share price such as support vector machine, regression, sentiments from different social websites like Twitter and Facebook, etc. which have some limitations. This study proposes a sentiment analysis model developed to infer the polarity of news articles related to a company. The process of collecting the dataset, as well as a diagram of the system architecture for the sentiment analysis engine used in this study is provided to readers.

Keywords: Sentiment analysis, stock markets, prediction, text mining, opinion, polarity, efficient market hypothesis

Cite this Article

Arun Joe Babulo S, Mary Dallfin Bruxella J, Kanimozhi JK. Stock Market Prediction Based on News Sentiments. Journal of Advances in Shell Programming. 2017; 4(2): 26–33p.