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The social signal

Author

Listed:
  • Cookson, J. Anthony
  • Lu, Runjing
  • Mullins, William
  • Niessner, Marina

Abstract

We examine social media attention and sentiment from three major platforms: Twitter, StockTwits, and Seeking Alpha. We find that, even after controlling for firm disclosures and news, attention is highly correlated across platforms, but sentiment is not: its first principal component explains little more variation than purely idiosyncratic sentiment. Using market events, we attribute differences across platforms to differences in users (e.g., professionals versus novices) and differences in platform design (e.g., character limits in posts). We also find that sentiment and attention contain different return-relevant information. Sentiment predicts positive next-day returns, but attention predicts negative next-day returns. These results highlight the importance of considering both social media sentiment and attention, and of distinguishing between different investor social media platforms.

Suggested Citation

  • Cookson, J. Anthony & Lu, Runjing & Mullins, William & Niessner, Marina, 2024. "The social signal," Journal of Financial Economics, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:jfinec:v:158:y:2024:i:c:s0304405x2400093x
    DOI: 10.1016/j.jfineco.2024.103870
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    More about this item

    Keywords

    Social media; Retail trading; Social finance;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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