Aggregated Sentiment Analysis of RSS News feeds, Biased Stock News and Twitter for Effective Stock Market Prediction
Abstract
Normally, stock market is volatile and complex and so predicting the stock movement is a great challenge. The proposed algorithm combines the sentiments of RSS news feeds, Twitter and Biased Stock news with the Stock level indicators. The proposed approach not only focuses on achieving the best results and also to reduce the inaccurate forecasting of stock prices. In the experimental study, the sensex prices of different companies, namely Arab Bank, Infosys, Reliance and TCS were collected. The stock level indicators of the above companies were calculated and they were correlated with the sentiments of RSS news feeds, twitter and biased stock news of the same company for a particular period of time. It was proved that our experimental study had improved the prediction accuracy considerably over standard prediction algorithms.