@inproceedings{15c8c4e4dc1f41949b786288d7d74252,
title = "Can online emotions predict the stock market in China?",
abstract = "Whether the online social media,like Twitter or its variant Weibo,can be a convincing proxy to predict the stock market has been debated for years,especially for China. However,as the traditional theory in behavioral finance states,the individual emotions can influence decision-makings of investors,so it is reasonable to further explore this controversial topic from the perspective of online emotions,which is richly carried by massive tweets in social media. Surprisingly,through thorough study on over 10 million stock-relevant tweets fromWeibo,both correlation analysis and causality test demonstrate that five attributes of the stock market in China can be competently predicted by various online emotions,like disgust,joy,sadness and fear. Specifically,the presented model significantly outperforms the baseline solutions on predicting five attributes of the stock market under the K-means discretization.We also employ this model in the scenario of realistic online application and its performance is further testified.",
keywords = "Causality test, Sentiment analysis, Social media, Stock market",
author = "Zhenkun Zhou and Jichang Zhao and Ke Xu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 17th International Conference on Web Information Systems Engineering, WISE 2016 ; Conference date: 08-11-2016 Through 10-11-2016",
year = "2016",
doi = "10.1007/978-3-319-48740-3\_24",
language = "英语",
isbn = "9783319487397",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "328--342",
editor = "Wojciech Cellary and Jianmin Wang and Mokbel, \{Mohamed F.\} and Hua Wang and Rui Zhou and Yanchun Zhang",
booktitle = "Web Information Systems Engineering – WISE 2016 - 17th International Conference, Proceedings",
address = "德国",
}