Stock Trend Forecasting Method Based on Sentiment Analysis and System Similarity Model

摘要：

This paper combine sentiment analysis based on system similarity model and Bayesian classification model to design a prediction system for the stock plate price trend analysis according to the Internet stock news and information. This system can automatically classified the stock news on the web and apply sentiment analysis to judge related comments and predict the price movements. By the way of cross-rotation test show that the system can effectively predict and analyze the stock market and have good stability.

关键词： stock prediction sentiment analysis Bayesian model system similarity model

作者: Kaihui Zhang Lei Li Peng Li Wenda Teng

作者单位: College of Economy and Management,Harbin University of Science and Technology,Harbin China School of Business,JiangNan University,Wuxi China College of Computer Science and Technology,Harbin University of Science and Technology,Harbin China

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 890-894

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）