Parametrizing Brexit: Mapping Twitter Political Space to Parliamentary Constituencies

Information, Communication, & Society, Forthcoming

34 Pages Posted: 30 Jan 2018

See all articles by Marco T. Bastos

Marco T. Bastos

City University London - School of Social Sciences

Dan Mercea

City University London - School of Social Sciences

Date Written: January 22, 2018

Abstract

In this paper, a proof of concept study is performed to validate the use of social media signal to model the ideological coordinates underpinning the Brexit debate. We rely on geographically-enriched Twitter data and a purpose-built, deep learning algorithm to map the political value space of users tweeting the referendum onto Parliamentary Constituencies. We find a significant incidence of nationalist sentiments and economic views expressed on Twitter, which persist throughout the campaign and are only offset in the last days when a globalist upsurge brings the British Twittersphere closer to a divide between nationalist and globalist standpoints. Upon combining demographic variables with the classifier scores, we find that the model explains 41% of the variance in the referendum vote, an indication that not only material inequality, but also ideological readjustments have contributed to the outcome of the referendum. We conclude with a discussion of conceptual and methodological challenges in signal-processing social media data as a source for the measurement of public opinion.

Keywords: Brexit, Twitter, Public Opinion, Machine Learning, Nationalism, Populism, Referendum

Suggested Citation

Bastos, Marco Toledo and Mercea, Dan, Parametrizing Brexit: Mapping Twitter Political Space to Parliamentary Constituencies (January 22, 2018). Information, Communication, & Society, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3106886

Marco Toledo Bastos (Contact Author)

City University London - School of Social Sciences ( email )

London
United Kingdom

Dan Mercea

City University London - School of Social Sciences ( email )

London
United Kingdom

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