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Fear and hope in financial social networks: Evidence from COVID-19

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  • Al Guindy, Mohamed

Abstract

This paper examines the diffusion of COVID-19 news on social media using a large sample of approximately 45 million tweets. Using textual analysis, I identify tweets containing COVID-19 news, and construct an index representing the intensity of Twitter discussions. Moreover, I use retweets and favorites as additional measures of investor attention to COVID-19. The results show that the intensity of Twitter discussions about COVID-19 (and about the treatment program) correspond to market returns. This suggests a role for financial social networks in transmitting information related to crises, such as COVID-19, and the resolution of crises.

Suggested Citation

  • Al Guindy, Mohamed, 2022. "Fear and hope in financial social networks: Evidence from COVID-19," Finance Research Letters, Elsevier, vol. 46(PA).
  • Handle: RePEc:eee:finlet:v:46:y:2022:i:pa:s1544612321003135
    DOI: 10.1016/j.frl.2021.102271
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    References listed on IDEAS

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    1. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    2. Pagano, Michael S. & Sedunov, John & Velthuis, Raisa, 2021. "How did retail investors respond to the COVID-19 pandemic? The effect of Robinhood brokerage customers on market quality," Finance Research Letters, Elsevier, vol. 43(C).
    3. Michael S. Drake & Darren T. Roulstone & Jacob R. Thornock, 2012. "Investor Information Demand: Evidence from Google Searches Around Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 50(4), pages 1001-1040, September.
    4. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    5. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    6. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    7. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," The Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
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    Cited by:

    1. Ling Jin & Jun Hyeok Choi & Saerona Kim & Kwanghee Cho, 2022. "Slack Resources, Corporate Performance, and COVID-19 Pandemic: Evidence from China," IJERPH, MDPI, vol. 19(21), pages 1-21, November.
    2. Ben Chamberlain & Zhangxin (Frank) Liu & Lee A. Smales, 2023. "Short interest and the stock market relation with news sentiment from traditional and social media sources," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 321-334, June.

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    More about this item

    Keywords

    Networks; Social media; Big Data; COVID-19;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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