#IStandWithDan versus #DictatorDan: the polarised dynamics of Twitter discussions about Victoria's COVID-19 restrictions

, , , , & (2021) #IStandWithDan versus #DictatorDan: the polarised dynamics of Twitter discussions about Victoria's COVID-19 restrictions. Media International Australia, 179(1), pp. 127-148.

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Description

In this article, we examine two interrelated hashtag campaigns that formed in response to the Victorian State Government’s handling of Australia’s most significant COVID-19 second wave of mid-to-late 2020. Through a mixed-methods approach that includes descriptive statistical analysis, qualitative content analysis, network analysis, computational sentiment analysis and social bot detection, we reveal how a small number of hyper-partisan pro- and anti-government campaigners were able to mobilise ad hoc communities on Twitter, and – in the case of the anti-government hashtag campaign – co-opt journalists and politicians through a multi-step flow process to amplify their message. Our comprehensive analysis of Twitter data from these campaigns offers insights into the evolution of political hashtag campaigns, how actors involved in these specific campaigns were able to exploit specific dynamics of Twitter and the broader media and political establishment to progress their hyper-partisan agendas, and the utility of mixed-method approaches in helping render the dynamics of such campaigns visible.

Impact and interest:

15 citations in Scopus
10 citations in Web of Science®
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ID Code: 207260
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Graham, Timothyorcid.org/0000-0002-4053-9313
Bruns, Axelorcid.org/0000-0002-3943-133X
Angus, Danielorcid.org/0000-0002-1412-5096
Hurcombe, Edwardorcid.org/0000-0002-5838-2019
Additional Information: Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project is funded by an internal grant from the Digital Media Research Centre, Queensland University of Technology (QUT).
Measurements or Duration: 22 pages
Keywords: clicktivism, Coronavirus, COVID-19, disinformation, hashtag activism, misinformation, multi-step flow model, social media, Twitter
DOI: 10.1177/1329878X20981780
ISSN: 1329-878X
Pure ID: 74442940
Divisions: Current > Research Centres > Centre for Data Science
Current > Research Centres > Digital Media Research Centre
Current > QUT Faculties and Divisions > Academic Division
Current > QUT Faculties and Divisions > Faculty of Science
Current > QUT Faculties and Divisions > Faculty of Creative Industries, Education & Social Justice
Current > Schools > School of Communication
Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project is funded by an internal grant from the Digital Media Research Centre, Queensland University of Technology (QUT).
Copyright Owner: © The Author(s) 2020.
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Deposited On: 12 Jan 2021 06:37
Last Modified: 04 Aug 2024 23:25