Abstract
With the advent of the Web2.0 era, social media can achieve the rapid transmission of information and reduce the information asymmetry. In our study, we selected social media of Sina Weibo because of its wide use in China. Through text mining technology, this paper we extracted total 22504 tweets related to real estate industry. We succeeded in classify microblog accounts and two clusters of social media users are selected: individual investors and official media. Based on two dimensions of attention and emotion, this paper discusses the influence of different users on the stock market. Interestingly, the empirical results show that (1) there is an inverse U-shaped curve between attention and stock return for both official media and investor which support the over-attention underperformance hypothesis. (2) We also find that both daily sentiment of official media and investor are positively correlated to stock return. Our study contributes to a better understanding of emotion and stock market, particularly based on Chinese microblog.
Recommended Citation
Sun, Yuan; Chen, Guangyue; Liu, Xuan; and Hao, Yunhong, "How Mood Affects The Stock Market: Empirical Evidence From Chinese Microblog" (2018). CONF-IRM 2018 Proceedings. 2.
https://aisel.aisnet.org/confirm2018/2