Keynote presented at the Symposium 'Indicators of Social Cohesion' at the Research Institute Social Cohesion, Hamburg, 25 Apr. 2024.

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Dynamics of Destructive Polarisation in
Mainstream and Social Media: The Case of the
Australian Voice to Parliament Referendum
Axel Bruns with important contributions from:
Australian Laureate Fellow Laura Vodden Katharina Esau Sebastian Svegaard
Digital Media Research Centre Tariq Choucair Samantha Vilkins Kate O’Connor Farfan
Queensland University of Technology Laura Lefevre Vishnu PS Carly Lubicz-Zaorski
Brisbane, Australia Ehsan Dehghan Kateryna Kasianenko
a.bruns@qut.edu.au
@snurb_dot_info | @snurb@aoir.social | @snurb.bsky.social

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► Implies that something is threatening
that cohesion…
Gesellschaftlicher Zusammenhalt?
Societal Cohesion?

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Can we simply blame our
platforms and their
algorithms?
Filter bubbles?
Echo chambers?
(https://commons.wikimedia.org/wiki/File:Eli_Pariser,_author_of_The_Filter_Bubble_-_Flickr_-_Knight_Foundation.jpg)

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Ready access to information
enables spread of ‘fake
news’, hyperpartisanship,
and polarisation.
(But also social connection
and community support.)
Hyperpartisans,
Hyperconnected
(https://twitter.com/bigfudge212121/status/1259317174776115201)

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The problem with an extraterrestrial-
conspiracy mailing list isn’t that it’s an echo
chamber; it’s that it thinks there’s a
conspiracy by extraterrestrials.
— David Weinberger, Salon, 21 Feb. 2004
(https://commons.wikimedia.org/wiki/File:David_Weinberger.jpg)

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(https://www.vice.com/de/article/pam5nz/deshalb-ist-filterblase-die-blodeste-metapher-des-internets)

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Image: Midjourney
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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Image: Midjourney
Forms of Polarisation

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(https://www.pewresearch.org/politics/2022/08/09/as-partisan-hostility-grows-signs-of-
frustration-with-the-two-party-system/pp_2022-08-09_partisan-hostility_01-08/)
(https://www.pewresearch.org/politics/2023/09/19/the-republican-and-
democratic-parties/pp_2023-09-19_views-of-politics_04-02/)

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Forms of Polarisation
• Polarisation at what levels?
• Micro: between individuals
• Meso: between groups
• Macro: across society
• Mass: involving everyone
• Elite: amongst formal political actors (however defined)
• See: Esau et al. (2023) — https://eprints.qut.edu.au/238775/
• (and chapter forthcoming in the Routledge Handbook of Political Campaigning)

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Forms of Polarisation
• Polarisation on what attributes?
• 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
• Interactional: manifested in choices to interact with or ignore other individuals/groups
• (and more…)

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Image: Midjourney
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.
Image: Midjourney

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(And also, are these the right / the only
symptoms of destructive polarisation?)
But:
How do we operationalise these
symptoms in empirical research?

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Case Study
(https://www.abc.net.au/news/2023-10-08/voice-polls-show-support-lower-than-republic-vote/102942468)

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• Indigenous rights and recognition:
• Complex topic since European arrival in 1788
• Indigenous Australians remain severely
disadvantaged
• Persistent lack of formal consultation
• Voice to Parliament:
• Endorsed in 2017 Uluru Statement from the Heart
• Commitment to referendum on a Voice in Anthony
Albanese’s 21 May 2022 election victory speech
• Referendum design revealed in March 2023
• Constitutional referendum held on 14 Oct. 2023
Proposed Constitutional Amendment:
Chapter IX Recognition of Aboriginal and Torres Strait Islander
Peoples
129 Aboriginal and Torres Strait Islander Voice
In recognition of Aboriginal and Torres Strait Islander peoples as the
First Peoples of Australia:
1. There shall be a body, to be called the Aboriginal and Torres Strait
Islander Voice;
2. The Aboriginal and Torres Strait Islander Voice may make
representations to the Parliament and the Executive Government of
the Commonwealth on matters relating to Aboriginal and Torres
Strait Islander peoples;
3. The Parliament shall, subject to this Constitution, have power to
make laws with respect to matters relating to the Aboriginal and
Torres Strait Islander Voice, including its composition, functions,
powers and procedures.
Case Study: Voice to Parliament Referendum

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Referendum Vote
• Voting modus:
• Compulsory for all registered voters
• Actual turnout: 89.95%
• Requirements for success:
• Majority of voters overall
• Majority of voters in majority of states
(4 of 6)
• Results:
• Overall: 40% Yes, 60% No
• 0 of 6 states
• Yes win only in Australian Capital
Territory
By Teratix - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=131601888

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Example: No Campaign’s Use of Fear and Doubt
“The campaign to sink the Voice has instructed volunteers
to use fear and doubt rather than facts to trump arguments
used by the Yes camp.” (Sydney Morning Herald)
Symptoms of Dysfunction:
Exclusion through
Emotions
(https://www.smh.com.au/politics/federal/no-campaign-s-fear-doubt-strategy-revealed-20230910-p5e3fu.html)

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Example: YouTube Videos Shared on Facebook
Explicitly conspiracist (and antisemitic) videos amongst the
YouTube video content shared most frequently in public
Facebook groups and pages.
Symptoms of Dysfunction:
Disproportionate Attention
to Extreme Voices

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Example: Sky News Australia Reporting
Many of the most widely shared videos from influential
conservative news source Sky News Australia made
explicitly conspiracist claims.
Symptoms of Dysfunction:
Discrediting and Dismissal
of Information
(https://www.skynews.com.au/opinion/peta-credlin/transfer-of-power-voice-has-very-little-to-do-with-supporting-indigenous-australians/video/597252c79e59d25cf3bfe0c423768dc1,
https://www.skynews.com.au/australia-news/sky-news-host-peta-credlin-exposes-labors-lie-on-the-uluru-statement-from-the-heart-under-freedom-of-information-act/news-story/f1539032a44c6658c2feb352b2ddea45,
https://www.skynews.com.au/opinion/andrew-bolt/youve-been-misled-real-agenda-of-the-voice-exposed-in-a-brawl/video/d2255bf53cb4c0223e990cabd1461f14)

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Example: Liberal Party ‘No’ Campaign on Instagram
Simple language, appeals to ignorance.
Symptoms of Dysfunction:
Erasure of Complexities
(https://www.instagram.com/p/CyMy7hFI1Kw/)

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Example: @mention network on Twitter*
Some separation into Yes/No camps, with continued
exchanges between the two sides – but often lack of
meaningful engagement between them.
Symptoms of Dysfunction:
Breakdown of
Communication
* Data obtained through NodeXL Twitter scraper, with limited completeness.
Red: exclusively using #VoteNo; green: exclusively using #VoteYes.

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Can new methods add more rigour
to the analysis?
⚠️ Work in Progress…
Towards a More Systematic Validation
and Diagnosis of These Symptoms?

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Current thinking:
Quantifying specific aspects of individual participant
activities, then identifying and interpreting similar patterns
at a group level.
* With particular thanks to Kateryna Kasianenko.
Beyond Qualitative
Interpretation:
Practice Mapping*
Image: Midjourney

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Twitter @mention network during Voice to Parliament campaign
Red: exclusively using #VoteNo; green: exclusively using #VoteYes.
Twitter interaction pattern similarity network – based on cosine similarity between
normalised interaction vectors per account, colours based on modularity detection.
Pro-Voice
campaigners
Labor
supporters
Anti-Voice
campaigners
Liberal / National
supporters

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• Account-to-account interactions
(relative to interactive affordances available
on any given social media platform)
• Account’s post content (topics, sentiment,
hashtags, named entities, etc.)
• Account’s use of sources (URLs, domains,
embedded videos and images, etc.)
• Account’s profile information (name,
description, etc.)
• Manually and computationally coded
information about the account and its posts
• …
Potential Patterns
to Operationalise
in Practice Mapping
Image: Midjourney

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Assessing Destructive Polarisation
• Key questions:
• Does practice mapping show distinct practices?
• What divergent patterns drive such distinctions?
• Do these patterns map onto one of the symptoms
of destructive polarisation?
• (Or: do they represent a new pattern that might be
seen as destructive – a new symptom?)
• How severe are these differences (i.e. how deeply
and destructively polarised is the situation)?
• How are these patterns evolving over time?
Image: Midjourney

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Thank you!
Image: Midjourney

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This research is supported by the Australian Research Council through the
Australian Laureate Fellowship project Determining the Dynamics of
Partisanship and Polarisation in Online Public Debate.
Acknowledgments