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Understanding the role of social media sentiment in identifying irrational herding behavior in the stock market

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  • Li, Tong
  • Chen, Hui
  • Liu, Wei
  • Yu, Guang
  • Yu, Yongtian

Abstract

This study examined the role of social media sentiment in identifying irrational herding behavior in the stock market. We selected the Chinese stock market, where majority are retail investors, as the object of analysis, and analyzed the sentiment of 227,353 microblog text messages through deep learning techniques and constructed the identification method of herd behavior. Results show that social media sentiment has a significant impact on irrational herding behavior in the stock market. The findings of the study complement the theory of investor behavior and can aid in investors' trading decisions and financial regulators’ policy recommendations.

Suggested Citation

  • Li, Tong & Chen, Hui & Liu, Wei & Yu, Guang & Yu, Yongtian, 2023. "Understanding the role of social media sentiment in identifying irrational herding behavior in the stock market," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 163-179.
    • Handle: RePEc:eee:reveco:v:87:y:2023:i:c:p:163-179
    DOI: 10.1016/j.iref.2023.04.016
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    1. Cai, Yi & Tang, Zhenpeng & Chen, Ying, 2024. "Can real-time investor sentiment help predict the high-frequency stock returns? Evidence from a mixed-frequency-rolling decomposition forecasting method," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    2. Maxim S. Faizulin, 2024. "Sentiment and Herd Behavior of Private Investors: A Cluster Analysis of the Russian Stock Market," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 95-113, August.
    3. Wu, Yanran & Wu, Shan & Xu, Fujia & Jiang, Jie, 2024. "Wisdom of crowds or awkward squad? Social interaction and the information efficiency of the Chinese capital market," Research in International Business and Finance, Elsevier, vol. 71(C).
    4. An Pham Ngoc Nguyen & Martin Crane & Thomas Conlon & Marija Bezbradica, 2024. "Herding Unmasked: Insights into Cryptocurrencies, Stocks and US ETFs," Papers 2407.08069, arXiv.org, revised Dec 2024.

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