4.1 Article

Social media bots and stock markets

Journal

EUROPEAN FINANCIAL MANAGEMENT
Volume 26, Issue 3, Pages 753-777

Publisher

WILEY
DOI: 10.1111/eufm.12245

Keywords

computational linguistics; investor sentiment; noise traders; social media bots; text classification

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This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.

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