140 characters to victory?: Using Twitter to predict the UK 2015 General Election. (March 2016)

• Record Type: Journal Article
• Authors: Burnap, Pete; Gibson, Rachel; Sloan, Luke; Southern, Rosalynd; Williams, Matthew
• Is Part Of: Electoral studies. Volume 41(2016:Mar.)
• Page Start: 230
• Page End: 233
• Publication Date: 2016-03
• Subjects: Election -- Forecasting -- Twitter -- Sentiment analysis; Elections -- Periodicals; Voting -- Periodicals; 324.6
• DOI: 10.1016/j.electstud.2015.11.017
• Languages: English
• ISSNs: 0261-3794

Abstract

Abstract: This paper uses Twitter data to forecast the outcome of the 2015 UK General Election. While a number of empirical studies to date have demonstrated striking levels of accuracy in estimating election results using this new data source, there have been no genuine i.e. pre-election forecasts issued to date. Furthermore there have been widely varying methods and models employed with seemingly little agreement on the core criteria required for an accurate estimate. We attempt to address this deficit with our 'baseline' model of prediction that incorporates sentiment analysis and prior party support to generate a true forecast of parliament seat allocation. Our results indicate a hung parliament with Labour holding the majority of seats. Highlights: We present a genuine forecast of a national election using Twitter data. We demonstrate that Twitter is a useful tool for electoral forecasting. Our forecast accurately predicts the top three parties in terms of vote share. Our findings suggest that Labour supporters were more active on Twitter. Geocoding of tweets is needed to accurately forecast outcomes for regional parties.