Currently, a new form of media, called Digital Interactive Media, has been popular in Chinese stock market. Investors can interact with listed companies directly. Therefore, it might be necessary to deconstruct and extract features of the interactive platform's information to understand the influence mechanism of digital platform on stock price fluctuations. This paper uses web crawling technology to obtain massive interactive information from Panorama from 2015 to 2019, extracts some valuable influencing factors through emotional quantification technology, and creates a Multiple Regression Model to explore effect of different emotional factors on stock price volatility. The empirical results show that the sentiment in investors' questions will not significantly affect correspondent stock prices, but the tone and sentiment of the response of listed companies will significantly influence stock prices trends, especially the price of the current trading day or next trading day. The robustness test and endogeneity test supports the research conclusions.


Paper Number 1320; Track Digital Innovation; Short Paper



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