The Relationship Between Social Attention and the Risk of Stock Price Collapse of Enterprises: Perspective from Baidu Tieba
DOI:
https://doi.org/10.61173/ajyr1865Keywords:
Social Media Attention, Stock Price Crash Risk, Baidu TiebaAbstract
With the rapid progress of the world economy, the problem of stock price collapse has become a major threat to the stable development of stock markets in various industries. Based on Baidu Tieba, this paper collects the stock price data of each listed company in the CSMAR database as the dependent variable NCSKEW_Mdeq, the total posts, total users and average repost number as the independent variables. Use Stata to conduct regression analysis on the two. As a result, it was found a significant negative link between Total Posts and Total Users and the dependent variable NCSKEW_Mdeq and there was no statistically significant link between Avg Repost Num and the dependent variable. This study provides a brand-new perspective for reducing the risk of stock price collapse in enterprises, aiming to explore and analyze the key factors that affect the stability of corporate stock prices, and thus provide clear direction and strong theoretical support for future research on protecting the interests of shareholders.
References
[1] Chen, J., Liu, S., & Wang, T. The China economy yearbook Volume 5: Analysis and forecast of China’s economy (1st ed.), 2011.
[2] SÜAR, A. The advantages of social media marketing against traditional media channels. Academic Journal of Information Technology,2017, 8(28): 21–44.
[3] Chen, Z., Zhang, R., Xu, T., Yang, Y., Wang, J., & Feng, T. Emotional attitudes towards procrastination in people: A largescale sentiment-focused crawling analysis. Computers in Human Behavior, 2020, 110:106-391.
[4] Lee, C. S. Online fraud victimization in China: A case study of Baidu Tieba. Victims & Offenders, 2021, 16(3): 343–362.
[5] Ma, H. User experience design of user-generated content products. In Design, user experience, and usability: Design thinking and methods. Springer International Publishing, 2016, 9746: 94–104
[6] Sornette, D. Why stock markets crash: Critical events in complex financial systems. Princeton University Press, 2017.
[7] Wang, H., Cao, F., & Ye, K. Supervision or tunneling: The shareholding ratio of major shareholders and the risk of stock price crash. Management World, 2015, (02): 45-57+187.
[8] Zhao, L., & Huang, H. The evolution of information disclosure patterns and the risk of stock price crash: Evidence based on the release of industry information disclosure guidelines. Finance and Economics (Caijing Luncong), 2022, (07): 79-89.
[9] Wang, Y., & Wang, X. The impact of corporate funds “divorcing from the real to the virtual” on the risk of stock price crash. Audit and Economic Research, 2022, 37(01): 94-105.
[10] Lu, J., & Qiu, Y. H. Does non-punitive regulation diminish stock price crash risk? Journal of Banking & Finance, 2023, 148: 1-17.
[11] Xu, Y., Xuan, Y., & Zheng, G. Internet searching and stock price crash risk: Evidence from a quasi-natural experiment. Journal of Financial Economics, 2021, 141(1): 255-275.
[12] Martellini, P., & Menzio, G. Declining search frictions, unemployment, and growth. Journal of Political Economy, 2020, 128(12): 4387-4437.
[13] Xiao, Q., & Shen, H. Media attention, heterogeneous beliefs of investors, and stock price synchronicity. Finance and Trade Research, 2021, 32(10): 99-110.
[14] Xu, N.X., Yu, S.Y., & Yi, Z.H. Herd behavior of institutional investors and the risk of stock price crash. Management World, 2013, (07): 31-43.
[15] Jiang, J., Qiu, J.C., Zhu, R., & Hu, H.F. Investor attention and the risk of stock price crash: Does it suppress or exacerbate? Securities Market Herald, 2020, (03): 69-78.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 by the authors.
This work is licensed under a Creative Commons Attribution 4.0 International License.
