Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2017, Vol. 53 ›› Issue (2): 273-278.DOI: 10.13209/j.0479-8023.2017.037

• Orginal Article • Previous Articles     Next Articles

Stock Index Prediction Based on Text Information

Li DONG, Zhongqing WANG, Deyi XIONG()   

  1. School of Computer Science and Technology, Soochow University, Suzhou 215006
  • Received:2016-07-21 Revised:2016-09-23 Online:2016-11-28 Published:2017-03-20
  • Contact: Deyi XIONG


董理, 王中卿, 熊德意()   

  1. 苏州大学计算机科学与技术学院, 苏州 215006
  • 通讯作者: 熊德意
  • 基金资助:


Sentiment analysis strategy was used to predict stock market index. Support vector machine was applied to construct predict model based on textual information (i.e., lexical information, sentimental words, and sentiment categories) extracted from social media and stock indicators. Experiment results show that the proposed method can obtain the best results, compared with many different predictive model.

Key words: stock index prediction, sentiment analysis, support vector regression (SVR)


基于情感分析方法, 对股票市场进行预测。将从社交媒体中抽取的文本信息(词信息、情感词信息和情感分类信息)与股票技术指标相结合, 利用支持向量回归构建模型。通过实验与多种预测方法进行比较, 结果表明该方法能够获得较为理想的预测结果。

关键词: 股票预测, 情感分析, 支持向量回归(SVR)

CLC Number: