Abstract
Financial and business news contain various information about different companies, stock markets and other financial information. This information could be useful for predicting the stock market movement. The aim of this study is to determine whether financial news could be used to predict the Malaysian stock market movement. The sentiment analysis and classification were done using Hybrid Naïve Bayes algorithm. The data for this study was collected from Genting Berhad for a period of 11 months. The method resulted in news classification accuracy of 68.75% and showed a correlation of 58.41% between historical stock price and the sentiment data.
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