@techreport{290d787e0b204ca9bcfa827689c2283f,
title = "Dundee Discussion Papers in Economics 293: Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair",
abstract = "Information extracted from social media has been used by academics, and increasingly by practitioners, to predict stock returns. But to what extent does social media output predict asset fundamentals, and not simply short-term returns? In this paper we analyse 13.8m posts on Twitter, and high-frequency betting data from Betfair, concerning English Premier League soccer matches in 2013/14. Crucially, asset fundamentals are revealed at the end of play. We find that the Tweets of certain journalists, and the tone of all Tweets, contain fundamental information not revealed in betting prices. In particular, Tweets aid in the interpretation of news during matches.",
keywords = "Social media, Prediction markets, Fundamentals, Sentiment, Mispricing",
author = "Alasdair Brown and Dooruj Rambaccussing and Reade, {J. James} and Giambattista Rossi",
year = "2016",
month = feb,
day = "17",
language = "English",
series = "Dundee Discussion Papers in Economics",
publisher = "University of Dundee",
number = "293",
type = "WorkingPaper",
institution = "University of Dundee",
}