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Fake It ‘Til You Make It: A Natural Experiment to Identify European Politicians’ Benefit from Twitter Bots

Published online by Cambridge University Press:  11 September 2020

BRUNO CASTANHO SILVA*
Affiliation:
University of Cologne
SVEN-OLIVER PROKSCH*
Affiliation:
University of Cologne
*Corresponding
Bruno Castanho Silva, Post-Doctoral Researcher, Cologne Center for Comparative Politics, University of Cologne, bcsilva@wiso.uni-koeln.de.
Sven-Oliver Proksch, Professor of Political Science and Chair for European and Multilevel Politics, Cologne Center for Comparative Politics, University of Cologne, so.proksch@uni-koeln.de.

Abstract

Social media giants stand accused of facilitating illegitimate interference with democratic political processes around the world. Part of this problem are malicious bots: automated fake accounts passing as humans. However, we lack a systematic understanding of which politicians benefit most from them. We tackle this question by leveraging a Twitter purge of malicious bots in July 2018 and a new dataset on Twitter activity by all members of national parliaments (MPs) in the EU in 2018. Since users had no influence on how and when Twitter purged millions of bots, it serves as an exogenous intervention to investigate whether some parties or politicians lost more followers. We find drops in follower counts concentrated among radical right politicians, in particular those with strong anti-EU discourse. This is the first set of empirical, causally identified evidence supporting the idea that the radical right benefits more from malicious bots than other party families.

Type
Letter
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association

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Footnotes

We would like to thank Danielle Pullan, Pit Rieger, Rebecca Kittel, Leonie Diffené, Felix Reich, Barbara Zucchi Nobre Silva, Jasmin Spekkers, Noam Himmelrath, Lennart Schürmann, and Lea Kaftan for excellent research assistance, and Leo Baccini, Jens Wäckerle, Bastian Becker, Ahmet Suerdem, participants of the PolText Conference at Waseda University in Tokyo, September 13–15, 2019, and the three anonymous reviewers for helpful comments and suggestions. All remaining errors are our own. This research has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy–EXC 2126/1–390838866. Replication files are available at the American Political Science Review Dataverse: https://doi.org/10.7910/DVN/PAMABU.

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