Publication Type

Journal Article

Version

publishedVersion

Publication Date

10-2017

Abstract

We use 23M Tweets related to the EU referendum in the UK to predict the Brexit vote. In particular, we use user-generated labels known as hashtags to build training sets related to the Leave/Remain campaign. Next, we train SVMs in order to classify Tweets. Finally, we compare our results to Internet and telephone polls. This approach not only allows to reduce the time of hand-coding data to create a training set, but also achieves high level of correlations with Internet polls. Our results suggest that Twitter data may be a suitable substitute for Internet polls and may be a useful complement for telephone polls. We also discuss the reach and limitations of this method.

Discipline

Models and Methods | Political Science | Social Media

Research Areas

Political Science

Publication

Statistics, Politics and Policy

Volume

8

Issue

1

First Page

85

Last Page

104

ISSN

2194-6299

Identifier

10.1515/spp-2017-0006

Publisher

De Gruyter

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1515/spp-2017-0006

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