Extraction of Keywords Related with Stock Price Change from Bloggers' Hot Topics

Abstract

This paper presents an extraction method of keywords related with actual changes of stock price from bloggers' hot topics. We realized the computer program to collect bloggers' hot topics about stocks and actual stock prices. Then, the important keywords, which have correlation with changes of the stock prices, are selected based on stochastic complexity. We classify information of stock price changes by using text classification method such as Naive Bayes method and decision tree learning. We confirm the effectiveness of our method through the classification experiment.