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FORECASTING WITH SOCIAL MEDIA: EVIDENCE FROM TWEETS ON SOCCER MATCHES
Author(s) -
Brown Alasdair,
Rambaccussing Dooruj,
Reade J. James,
Rossi Giambattista
Publication year - 2018
Publication title -
economic inquiry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.823
H-Index - 72
eISSN - 1465-7295
pISSN - 0095-2583
DOI - 10.1111/ecin.12506
Subject(s) - social media , league , microblogging , variety (cybernetics) , advertising , economics , sentiment analysis , tone (literature) , business , computer science , world wide web , artificial intelligence , physics , astronomy , art , literature
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)