Paper by Axel Bruns, Katharina Esau, Tariq Choucair, Sebastian Svegaard, and Samantha Vilkins, presented at the ECREA Political Communication conference in Berlin, 1 Sep. 2023.

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Determining the Drivers and Dynamics
of Partisanship and Polarisation in
Online Public Debate
Axel Bruns, Katharina Esau, Tariq Choucair, Sebastian Svegaard, Samantha Vilkins
Digital Media Research Centre
Queensland University of Technology
Brisbane, Australia
a.bruns|katharina.esau|tariq.choucair|sebastian.svegaard|samantha.vilkins@qut.edu.au
@snurb_dot_info | @snurb@aoir.social | @snurb.bsky.social

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Polarisation

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Our Project
• Australian Laureate Fellowship (2022-27)
• Determining the Drivers and Dynamics of Partisanship and Polarisation in Online Public
Debate
• Digital Media Research Centre, Queensland University of Technology, Brisbane, Australia
• 4 postdocs, 4 + 4* PhD students, 1 data scientist
• Cross-national comparisons (intended: AU, US, UK, DE, DK, CH, probably + BR, PE, CA)
• Longitudinal analysis over the course of the project
* Starting in 2024 – interested? Get in touch! (a.bruns@qut.edu.au)

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(It’s complicated.)
Assessing Polarisation
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(https://www.pewresearch.org/politics/2017/10/05/1-partisan-divides-over-political-values-widen/)

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Forms of Polarisation
• Polarisation at what level?
• Issue-based: disagreements over specific policy settings
• Ideological: fundamental differences based on political belief systems
• Affective: political beliefs turned into deeply felt in-group / out-group identity
• Perceived: view of society, as based on personal views and media reporting
• Interpretive: reading of issues, events, and media coverage based on personal views
• (and more…)
• (chapter forthcoming in the Routledge Handbook of Political Campaigning)

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A Problem? (When?)

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Agonism? Polarisation? Dysfunction?
• How bad is it, exactly?
• All politics is polarised (just not to the point of dysfunction)
• Much (most?) politics is multipolar, not just left/right
• When does mild antagonism turn into destructive polarisation?
• We suggest five symptoms (Esau et al., 2023):
a) breakdown of communication;
b) discrediting and dismissing of information;
c) erasure of complexities;
d) exacerbated attention and space for extreme voices;
e) exclusion through emotions.
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Dimensions of
Polarisation
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1. News Coverage
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Our Approach
• Is there a robust empirical way to do this, beyond feelpinions?
• Plans:
• Full-text access to (online, text-based) news content across target countries
• Manual and computational analysis of:
• Topical focus and voices featured in coverage
• Language, tone, sentiment of coverage
• Framing of actors, issues, events in the news
• Also: experimenting with the use of AI (LLMs) in content coding
• Exploration of systematic divergences between news outlets

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2. News Audiences
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15. Park, Sora, Caroline Fisher, Kieran McGuinness, Jee Young Lee, and Kerry McCallum. 2021. Digital News Report: Australia 2021. Canberra: News and Media Research Centre. https://doi.org/10.25916/KYGY-S066.

16. Park, Sora, Caroline Fisher, Kieran McGuinness, Jee Young Lee, and Kerry McCallum. 2021. Digital News Report: Australia 2021. Canberra: News and Media Research Centre. https://doi.org/10.25916/KYGY-S066.

17. {comparison across political systems}
News Engagement Polarisation
Faris, Robert, Hal Roberts, Bruce Etling, Nikki Bourassa, Ethan Zuckerman, and Yochai Benkler. 2017. “Partisanship, Propaganda, and Disinformation: Online Media and the 2016 U.S. Presidential Election.” Berkman Klein Center Research Publication 2017–6. Rochester, NY: Social Science Research Network. https://papers.ssrn.com/abstract=3019414.

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Our Approach
• Can we capture news audience engagement patterns?
• Plans:
• Long-term generic news sharing data (for Twitter, Facebook; other platforms tbd)
• ATNIX, DETNIX, NOTNIX, FakeNIX
• Correlation with likely political positioning (e.g. MP-MPAS approach: Giglietto et al., 2019)
• Exploration of typical news sharing repertoires and their disjunctures
• Can we move beyond active sharing, and towards more passive encounters?
• Plus: potential use of primary and secondary (e.g. DNR) survey data

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3. Public Discourse

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Adamic & Glance (2005)
Williams et al. (2015)

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US progressives
US conservatives
France /
Germany
Italy
Brazil
India
alternative
health
conspiracies
UK
alternative
finance
Nodes: public pages, groups, verified profiles / domains in posts
Size: weighted in-degree
Colour: weighted in-degree
FakeNIX domain posts, 1 Jan. 2016 to 31 Mar. 2021
Angus, D., Bruns, A., Hurcombe, E., & Harrington, S. (2021). ‘Fake news’ on Facebook: a
large-scale longitudinal study of problematic link-sharing practices from 2016 to 2020.
In Selected Papers in Internet Research 2021: Research from the Annual Conference of the
Association of Internet Researchers AoIR - Association of Internet
Researchers. https://doi.org/10.5210/spir.v2021i0.12089

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Our Approach
• Case studies of major public debates, with cross-national comparisons where possible
• Plans:
• Long history of research into online public debates, especially on social media
• Issue mapping / controversy mapping approaches well established
• Extension from older platforms (Twitter, Facebook) to new spaces (Telegram, TikTok, …)
• and to cross-platform analysis approaches, tracing connections and flows
• Network, content, sentiment, timeseries analyses, …
• Also: public debates in per se apolitical ‘third spaces’ (Wright et al., 2016)

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4. Networks

24. The Australian Twittersphere, 2016
4m known Australian accounts
Network of follower connections
Filtered for degree ≥1000
255k nodes (6.4%), 61m edges
Edges not shown in graph
(From Bruns, Moon, Münch, and Sadkowsky, 2017.)

25. Teen Culture
Aspirational
Sports
Netizens
Arts & Culture
Politics
Television
Fashion
Popular Music
Food & Drinks
Agriculture Activism
Porn
Education
Cycling
News &
Generic
Hard Right
Progressive
South
Australia
Celebrities
Horse Racing
4m known Australian accounts
Network of follower connections
Filtered for degree ≥1000
255k nodes (6.4%), 61m edges
Edges not shown in graph

26. Süddeutsche Zeitung (2017)
Political Partisans’ Other Facebook Interests

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Our Approach
• Is it still possible to map underlying online social networks, even after the APIcalypse?
• Plans:
• Facebook, Twitter: no longer possible to replicate past studies (at least for now)
• Emerging methodologies for Telegram and other newer platforms
• Data donation-based research possible but necessarily very uneven
• But: feasibility substantially dependent on future developments in social media landscape

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Thank you!

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Inputs to this were supported by the ARC Laureate Fellowship project Determining the Dynamics of
Partisanship and Polarisation in Online Public Debate, ARC Future Fellowship project Understanding
Intermedia Information Flows in the Australian Online Public Sphere, the ARC LIEF project TrISMA:
Tracking Infrastructure for Social Media Analysis, and the ARC Discovery projects Journalism beyond
the Crisis: Emerging Forms, Practices, and Uses and Evaluating the Challenge of 'Fake News' and
Other Malinformation.
Facebook data are provided courtesy of CrowdTangle.
Acknowledgments