Textual Sentiment of Chinese Microblog Toward the Stock Market

Ning Wang, Shanhui Ke (), Yibo Chen (), Tao Yan () and Andrew Lim ()
Additional contact information
Ning Wang: Department of Information Management, School of Management, Shanghai University, No. 333, Nanchen Rd., Shanghai, China
Shanhui Ke: Department of Information Management, School of Management, Shanghai University, No. 333, Nanchen Rd., Shanghai, China
Yibo Chen: #x2020;Shanghai Liangyou Asset Management Company Limited, Shanghai, China
Tao Yan: #x2021;Department of Management Science, School of Management, University of Science and Technology of China, China
Andrew Lim: #xA7;Department of Industrial Systems Engineering, National University of Singapore, Singapore

International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 02, 649-671

Abstract: In this paper, text mining and statistical models are deployed to explore the relationship between the Shanghai Stock Exchange Composite Index (SSECI) and the collective emotions of individual investors. The emotions of individual investors are quantified by extracting and aggregating investor online posts that contain finance-related keywords. To identify a set of finance-related keywords, three years of blogs from a famous financial blog site are segmented by an automatic text segmentation method; meanwhile, in the literature of social media, people typically select keywords manually. Posts that discuss the keywords are extracted out of all types of topics from Sina Weibo, the largest microblog platform in China. Statistical results reveal the relationship between daily posts and daily opening prices with a one-day lag, which indicates the existence of information (news) propagation lag. This study contributes to the existing literature by demonstrating that the microblog sentiment level reports can be quantitatively incorporated as a proxy to provide valuable support to portfolio decision making.

Keywords: Microblog; Chinese stock market; textual sentiment; emotions of investors (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219622019500068

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