FORECASTING WITH SOCIAL MEDIA: EVIDENCE FROM TWEETS ON SOCCER MATCHES.
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 contemporane...
| Published in: | Economic Inquiry Vol. 56; no. 3; pp. 1748 - 1764 |
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| Main Authors: | , , , |
| Format: | Article |
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Wiley-Blackwell
Jul2018
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=129933567&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 129933567 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00952583 EIQ jtl: Economic Inquiry issn: 00952583 maglogo: Y pubinfo: dt: Jul2018 vid: 56 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 129933567 10.1111/ecin.12506 ppf: 1748 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P size: 491KB tig: atl: FORECASTING WITH SOCIAL MEDIA: EVIDENCE FROM TWEETS ON SOCCER MATCHES. aug: au: Brown, Alasdair Rambaccussing, Dooruj Reade, J. James Rossi, Giambattista affil: School of Economics, University of East Anglia, Norwich, NR4 7TJ, UK Economic Studies, University of Dundee, Dundee, DD1 4HN, UK School of Economics, University of Reading, Reading, RG6 6AA, UK Department of Management, Birkbeck College, University of London, London, WC1E 7HX, UK su: Forecasting Social media Microblogs Soccer tournaments Evidence sug: subj: Forecasting Social media Microblogs Soccer tournaments Evidence ab: 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) pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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