The Filter in Our (?) Heads: Digital Media and Polarisation

New Research Culture lecture at the Helsinki Institute for Social Sciences and Humanities, 18 Sep. 2024.

1. The Filter in Our (?) Heads: Digital Media and Polarisation Prof. Axel Bruns Australian Laureate Fellow QUT Digital Media Research Centre [email protected] | @snurb_dot_info | @[email protected] | @snurb.bsky.social

2. Image: Midjourney Polarisation

3. (https://www.politico.com/news/2021/01/11/guards-lament-helplessness-capitol-riot-457877)

4. (https://www.reuters.com/world/us/53-republicans-view-trump-true-us-president-reutersipsos-2021-05-24/)

5. (https://www.theaustralian.com.au/breaking-news/jacquie-lambie-condemns-unaustralian-shrine-protesters/news-story/7a7b98222c26f7bda5dafe3d0a6e6ce6)

6. (https://www.theaustralian.com.au/commentary/coronavirus-our-loony-protesters-are-among-the-looniest/news-story/313cb4ac0ceabeb55d819dc25d35b895)

7. Polarisation and Hyperpartisanship Image: Midjourney

8. For too many of us it’s become safer to retreat into our own bubbles, whether in our neighborhoods, or on college campuses, or places of worship, or especially our social media feeds , surrounded by people who look like us and share the same political outlook and never challenge our assumptions. — farewell speech, 11 Jan. 2017 (https://www.harpersbazaar.com/culture/film-tv/news/a19883/president-obamas-farewell-address-best-quotes/)

9. 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)

10. admscentre.org.au/ searchexperience

11. 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, M ü nch , and Sadkowsky, 2017 . )

12. 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

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

14. Connectivity, Not Disconnection Image: Midjourney

15. 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)

16. 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)

17. (https://edition.cnn.com/videos/business/2021/09/19/how-do-your-own-research-hurts-americas-covid-response.cnn)

18. Hate-Reading Gentzkow, M., & Shapiro, J. M. (2011). Ideological Segregation Online and Offline. The Quarterly Journal of Economics , 126 , 1799–1839. https://doi.org/10.1093/qje/qjr044 Also see: Roberts, J., & Wahl-Jorgensen, K. (2020). Breitbart’s Attacks on Mainstream Media: Victories, Victimhood, and Vilification. In Affective Politics of Digital Media . Routledge.

19. How they imagine it… What it’s really like… How they imagine it… Images: Midjourney

20. Can We Blame ‘Fake News’? Image: Midjourney

21. (https://theconversation.com/we-live-in-an-age-of-fake-news-but-australian-children-are-not-learning-enough-about-media-literacy-141371)

22. Social, fringe, and mainstream media are intensely interconnected. (See Bruns, Hurcombe, Harrington, and Jude, 2021 .)

23. (https://firstdraftnews.org/training/)

24. This, but with a different system of coordinates, also drives conspiracy theories. Weaponising Media Literacy (https://britannicalearn.com/blog/britannica-tackles-media-literacy/)

25. ‘Fake News’ Is the Symptom, Not the Cause Put simply, studying fans and anti-fans in politics shifts the question from which news and information we believe to which news and information we choose to believe. — Cornel Sandvoss, “The Politics of Against” (2019) (…and to share!)

26. (It’s complicated.) Assessing Polarisation Image: Midjourney

27. (https://www.pewresearch.org/politics/2017/10/05/1-partisan-divides-over-political-values-widen/)

28. 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…)

29. 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 ): breakdown of communication; discrediting and dismissing of information; erasure of complexities; exacerbated attention and space for extreme voices; exclusion through emotions. Image: Midjourney

30. 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. How extreme is this, by comparison with other cases? Symptoms of Dysfunction: Breakdown of Communication * Data obtained through NodeXL Twitter scraper, with limited completeness. Red: exclusively using #VoteNo; green: exclusively using #VoteYes. Conventional Network Map

31. Example: @mention practice network on Twitter* Clear separation into Yes/No camps, with distinct and different practices on the two sides – indicating lack of meaningful engagement between them. How extreme is this, by comparison with other cases? Symptoms of Dysfunction: Breakdown of Communication * Data obtained through NodeXL Twitter scraper, with limited completeness. Twitter interaction practices 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 Practice Mapping

32. Example: Liberal Party ‘No’ Campaign on Instagram Simple language, appeals to ignorance. How might we operationalise this at scale? Sentence structure, semiotic analysis? Symptoms of Dysfunction: Erasure of Complexities ( https://www.instagram.com/p/CyMy7hFI1Kw/ )

33. Example: Sky News Australia Reporting Many of the most widely shared videos from influential conservative news source Sky News Australia made explicitly conspiracist claims. Distinct language choices and othering of opponents. 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 )

34. 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. Analysis of (audience and media) attention distribution. Symptoms of Dysfunction: Disproportionate Attention to Extreme Voices

35. 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 ) Detection of affective and emotional language choices. Symptoms of Dysfunction: Exclusion through Emotions ( https://www.smh.com.au/politics/federal/no-campaign-s-fear-doubt-strategy-revealed-20230910-p5e3fu.html )

36. 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

37. If we identify these symptoms: what can we do about them?

38. ( Image by Markus Spiske on Unsplash.com ) Thank you

39. Inputs to this were supported by the ARC Laureate Fellowship project 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 . The Australian Search Experience project is supported by the Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S). Facebook data were provided courtesy of CrowdTangle. Acknowledgments