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FORECASTING WITH SOCIAL MEDIA: EVIDENCE FROM TWEETS ON SOCCER MATCHES
Authors:Alasdair Brown  Dooruj Rambaccussing  J James Reade  Giambattista Rossi
Institution:1. +441603591131;2. School of Economics, University of East Anglia, Norwich, UK;3. +441382385318;4. Economic Studies, University of Dundee, Dundee, UK;5. +441183785062;6. School of Economics, University of Reading, Reading, UK
Abstract:Social media is now used as a forecasting tool by a variety of firms and agencies. But how useful are such data in forecasting outcomes? Can social media add any information to that produced by a prediction/betting market? We source 13.8 million posts from Twitter, and combine them with contemporaneous Betfair betting prices, to forecast the outcomes of English Premier League soccer matches as they unfold. Using a microblogging dictionary to analyze the content of Tweets, we find that the aggregate tone of Tweets contains significant information not in betting prices, particularly in the immediate aftermath of goals and red cards. (JEL G14, G17)
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