News or Noise? Using Twitter to Identify and Understand Company‐Specific News Flow
40 Pages Posted: 20 Oct 2014
Date Written: September/October 2014
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.
Keywords: event study, news events, information leakage, market reaction, computational linguistics
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