Topic Modeling based Sentiment Analysis on Social Media for Stock Market Prediction

被引:0
|
作者
Thien Hai Nguyen [1 ]
Shirai, Kiyoaki [1 ]
机构
[1] Japan Adv Inst Sci & Technol, Sch Informat Sci, 1-1 Asahidai, Nomi, Ishikawa 9231292, Japan
关键词
NOISE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The goal of this research is to build a model to predict stock price movement using sentiments on social media. A new feature which captures topics and their sentiments simultaneously is introduced in the prediction model. In addition, a new topic model TSLDA is proposed to obtain this feature. Our method outperformed a model using only historical prices by about 6.07% in accuracy. Furthermore, when comparing to other sentiment analysis methods, the accuracy of our method was also better than LDA and JST based methods by 6.43% and 6.07%. The results show that incorporation of the sentiment information from social media can help to improve the stock prediction.
引用
收藏
页码:1354 / 1364
页数:11
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