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How the far-right polarises Twitter: ‘hashjacking’ as a disinformation strategy in times of COVID-19

Abstract:
Twitter influences political debates. Phenomena like fake news and hate speech show that political discourses on social platforms can become strongly polarised by algorithmic enforcement of selective perception. Some political actors actively employ strategies to facilitate polarisation on Twitter, as past contributions show, via strategies of ‘hashjacking’(The use of someone else’s hashtag in order to promote one’s own social media agenda.). For the example of COVID-19 related hashtags and their retweet networks, we examine the case of partisan accounts of the German far-right party Alternative für Deutschland (AfD) and their potential use of ‘hashjacking’ in May 2020. Our findings indicate that polarisation of political party hashtags has not changed significantly in the last two years. We see that right-wing partisans are actively and effectively polarising the discourse by ‘hashjacking’ COVID-19 related hashtags, like #CoronaVirusDE or #FlattenTheCurve. This polarisation strategy is dominated by the activity of a limited set of heavy users. The results underline the necessity to understand the dynamics of discourse polarisation, as an active political communication strategy of the far-right, by only a handful of very active accounts.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-030-93413-2_9

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Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-0713-6010


Publisher:
Springer
Host title:
Complex Networks and Their Applications X. Complex Networks 2021
Pages:
100-111
Series:
Studies in Computational Intelligence
Series number:
1016
Publication date:
2022-01-01
Event title:
International Conference on Complex Networks and Their Applications
Event location:
Madrid, Spain
Event website:
https://2021.complexnetworks.org/
Event start date:
2021-11-30
Event end date:
2021-12-02
DOI:
EISSN:
1860-9503
ISSN:
1860-949X
EISBN:
978-3-030-93413-2
ISBN:
978-3-030-93412-5


Language:
English
Keywords:
Pubs id:
1236264
Local pid:
pubs:1236264
Deposit date:
2022-11-15
ARK identifier:

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