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Herding and investor sentiment after the cryptocurrency crash: evidence from Twitter and natural language processing

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  • Michael Cary

    (Virginia Tech)

Abstract

Although the 2022 cryptocurrency market crash prompted despair among investors, the rallying cry, “wagmi” (We’re all gonna make it.) emerged among cryptocurrency enthusiasts in the aftermath. Did cryptocurrency enthusiasts respond to this crash differently compared to traditional investors? Using natural language processing techniques applied to Twitter data, this study employed a difference-in-differences method to determine whether the cryptocurrency market crash had a differential effect on investor sentiment toward cryptocurrency enthusiasts relative to more traditional investors. The results indicate that the crash affected investor sentiment among cryptocurrency enthusiastic investors differently from traditional investors. In particular, cryptocurrency enthusiasts’ tweets became more neutral and, surprisingly, less negative. This result appears to be primarily driven by a deliberate, collectivist effort to promote positivity within the cryptocurrency community (“wagmi”). Considering the more nuanced emotional content of tweets, it appears that cryptocurrency enthusiasts expressed less joy and surprise in the aftermath of the cryptocurrency crash than traditional investors. Moreover, cryptocurrency enthusiasts tweeted more frequently after the cryptocurrency crash, with a relative increase in tweet frequency of approximately one tweet per day. An analysis of the specific textual content of tweets provides evidence of herding behavior among cryptocurrency enthusiasts.

Suggested Citation

  • Michael Cary, 2024. "Herding and investor sentiment after the cryptocurrency crash: evidence from Twitter and natural language processing," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    • Handle: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-024-00663-x
    DOI: 10.1186/s40854-024-00663-x
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    More about this item

    Keywords

    Bitcoin; Cryptocurrency; Herding; Investor sentiment; Natural language processing; Sentiment analysis; Twitter;
    All these keywords.

    JEL classification:

    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • G53 - Financial Economics - - Household Finance - - - Financial Literacy

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