News or Noise? Using Twitter to Identify and Understand Company-specific News Flow

News or Noise? Using Twitter to Identify and Understand Company-specific News Flow

This study presents a methodology for identifying a broad range of real‐world news events based on microblogging messages. Applying computational linguistics to a unique dataset of more than 400,000 S&P 500 stock‐related Twitter messages, we distinguish between good and bad news and demonstrate...

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Veröffentlicht in:Journal of business finance & accounting 2014-09, Vol.41 (7-8), p.791-830
Hauptverfasser: Sprenger, Timm O., Sandner, Philipp G., Tumasjan, Andranik, Welpe, Isabell M.
Format: Artikel
Sprache:eng
Schlagworte:
Blogs
computational linguistics
Computational methods
event study
information leakage
Instant messaging
market reaction
Messages
Methodology
News
news events
News media
Securities markets
Social networks
Stock exchange
Stock returns
Studies
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Zusammenfassung:This study presents a methodology for identifying a broad range of real‐world news events based on microblogging messages. Applying computational linguistics to a unique dataset of more than 400,000 S&P 500 stock‐related Twitter messages, we distinguish between good and bad news and demonstrate that the returns prior to good news events are more pronounced than for bad news events. We show that the stock market impact of news events differs substantially across different categories.
ISSN:0306-686X
1468-5957
DOI:10.1111/jbfa.12086