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Predicting the Brexit Vote by Tracking and Classifying Public Opinion Using Twitter Data

Amador Diaz Lopez, Julio Cesar and Collignon-Delmar, Sofia and Benoit, Kenneth and Matsuo, Akitaka (2017) 'Predicting the Brexit Vote by Tracking and Classifying Public Opinion Using Twitter Data.' Statistics, Politics and Policy, 8 (1). ISSN 2151-7509

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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.

Item Type: Article
Divisions: Faculty of Social Sciences
Faculty of Social Sciences > Government, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 23 Jul 2021 07:16
Last Modified: 06 Jan 2022 14:06
URI: http://repository.essex.ac.uk/id/eprint/25639

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