Divisive Data

deadline for submissions: 
August 17, 2020
full name / name of organization: 
Dr. Luke Munn

[ Context: Big Data & Society has issued a call for Special Theme Proposals. I will be proposing “Divisive Data” as a special theme. This initial call is to gather a list of interested contributors, along with titles and abstracts of articles, to submit to BD&S. ]

The promise of the internet was a promise of connection. Networked technologies would erase the physical and cultural space that separated us. Digital communications would unite us like never before. Online platforms would “bring the world closer together” (Zuckerberg 2017). Communication technologies would collapse boundaries, encourage dialogue, and facilitate mutual understanding.

Yet today data has become divisive. Data is used to separate certain groups, to sharpen their differences, and to weaponize their harassment. On social media, personalized data forms filter bubbles (Pariser 2012; Geschke et al. 2018), confirming our views while condemning those we disagree with. Rather than fostering a common consensus or public discourse, data-driven algorithms fragment society into niche groups and atomized individuals. When these publics do interact, it is often in highly antagonistic ways. Predicated on the metrics of “engagement”, platforms incentivize content that is emotive and controversial (Munn 2020 forthcoming). On the web, outrage and lies win, spreading faster and further than other content (Vosoughi et al. 2018). These polarizing posts trigger anger in users, driving views, shares, and comments. Communication platforms remove barriers to expressing this anger, allowing users to lash out to a large audience through a few mouse clicks (Crockett 2017).

Divisive data can again be witnessed in the recent rise of the radical right. In the last ten years, the far-right has reinvented itself, recasting racist, sexist, and xenophobic ideologies into novel forms. Information technologies have been key to this reinvention, enabling forms of digital hate to be carefully calibrated and widely distributed. The sociotechnical affordances of spaces like 4chan or Discord allow manifestos to spread and memes to be reworked (Wagner and Schwarzenegger 2020, Schmitt et al. 2020). The thousands of posts swirling in these spaces are an ideologically influential form of “big data”, but one that challenges typical associations with Big Tech (e.g. Google, Amazon, Apple) or Big Government (e.g. the NSA, 5 Eyes, Palantir). On mainstream platforms like YouTube, data-driven recommendations have come under fire. Scholars, journalists, and ex-radicals have noted how users are gradually recommended more extremist, divisive content (Naughton 2018, Nicas 2018, Tufekci 2018). Personalized data forms a pathway for radicalisation (Ribeiro et al. 2019), or a pipeline for the alt-right (Munn 2019). These technical affordances piggyback on the strong social ecosystems of the reactionary right (Lewis 2018).

These dynamics bring into focus the stakes of data broadly understood. As our everyday life becomes increasingly mediated through digital technologies, data forms a powerful and pervasive environment that shapes individuals on an ideological and psychological level. These environments enable communities to target the racial or sexual “other”, to amplify hate against them, and to direct this hate into forms of verbal and physical aggression. This is not an abstract issue, but a painfully present one. Indeed, violent attacks such as synagogue shootings (Pittsburgh and Halle), pipebombs (the MAGA bomber) and a mosque shooting (Christchurch) have demonstrated what could be understood as the natural “endpoint” of these data-amplified processes. Hate-filled data contributes toward hateful individuals.

How do data-driven processes and environments contribute to the recent rise of hate? How are racist, sexist, and xenophobic ideologies reworked and amplified by the unique affordances of digital technologies? And how might individuals and organisations critique and effectively counteract these growing threats? These are the key questions this issue centers around. The issue will aim to present a diverse mix of articles that roughly correspond to the following themes:

Spreading Hate

  • ●  The role of online platforms, social media, and other technical environments in fostering group-based hate, with a focus on data features, structures, and processes

  • ●  Data-driven (but theoretically aware) analyses of newer radical right spaces (e.g. Gab, Voat, BitChute) or appropriated spaces (e.g. Twitch, Discord)

  • ●  Contemporary examples of data-driven bubbles and their social fallout

  • ●  Tracing the data-driven circulation of a particular meme or ideology

Theorizing Hate

  • ●  Broader theorisations of how data architectures and affordances amplify hate

  • ●  How data’s ability to “make a difference” (Bateson 1972) amplifies homophily (Chun

    2018a; 2018b) and fosters division and discord

  • ●  Situating today’s divisive data in the “data” (broadly understood) of the past

Countering Hate

  • ●  Examples of communities adapting existing functionality to foster more inclusive spaces

  • ●  Redesigning data environments/architectures/logics to counteract hate and extremism

 The special theme will feature a maximum of 6 original research articles (max 10,000 words), and a maximum of 4 commentaries (max 3000 words). The commentaries would be ideal places to point to emergent dynamics in this space, to introduce new research concepts, or to stage a broader intervention that draws together diverse themes.

To register your interest, email Dr. Luke Munn (l.munn@westernsydney.edu.au) with an article title, a short abstract (<250 words), and an indication of whether this would be an original research article or a commentary. The deadline for submissions is August 17.

 

 

References:

Chun, Wendy Hui Kyong. 2018a. “Queerying Homophily.” In Pattern Discrimination, edited by Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer, and Hito Steyerl, 59–97. Lüneburg, Germany: Meson Press.https://mediarep.org/handle/doc/13259.

———. 2018b. “Critical Data Studies or How to Desegregate Networks.” Presented at the CHCI 2018, Charlottesville, VA, July 31.https://www.youtube.com/watch?v=Qhp80UXTvaQ.

Crockett, M. J. 2017. “Moral Outrage in the Digital Age.” Nature Human Behaviour 1 (11): 769–71.https://doi.org/10.1038/s41562-017-0213-3.

Geschke, Daniel, Jan Lorenz, and Peter Holtz. 2019. “The Triple-Filter Bubble: Using Agent-Based Modelling to Test a Meta-Theoretical Framework for the Emergence of Filter Bubbles and Echo Chambers.” British Journal of Social Psychology 58 (1): 129–49.https://doi.org/10.1111/bjso.12286.

Lewis, Rebecca. 2018. “Alternative Influence: Broadcasting the Reactionary Right on YouTube.” New York: Data & Society.https://datasociety.net/wp-content/uploads/2018/09/DS_Alternative_Influence.pdf.

Munn, Luke. 2019. “Alt-Right Pipeline: Individual Journeys to Extremism Online.” First Monday 24 (6).https://doi.org/10.5210/fm.v24i6.10108.

———. 2020 forthcoming. “Angry by Design: Technical Architectures and Toxic Communication.” Edited by Michael Grimshaw. Humanities & Social Sciences Communications, Digital Hate and (Anti-)Social Media, 7 (1).

Naughton, John. 2018. “However Extreme Your Views, You’re Never Hardcore Enough for YouTube.” The Guardian, September 23, 2018.https://www.theguardian.com/commentisfree/2018/sep/23/how-youtube-takes-you-to-extremes-when-it-comes-to-major-news-events.

Nicas, Jack. 2018. “How YouTube Drives People to the Internet’s Darkest Corners.” Wall Street Journal, February 7, 2018.https://www.wsj.com/articles/how-youtube-drives-viewers-to-the-internets-darkest-corners-1518020478.

Pariser, Eli. 2012. The Filter Bubble. London: Penguin Books.

Ribeiro, Manoel Horta, Raphael Ottoni, Robert West, Virgílio A. F. Almeida, and Wagner Meira. 2019. “Auditing Radicalization Pathways on YouTube.” ArXiv:1908.08313 [Cs], December.http://arxiv.org/abs/1908.08313.

Schmitt, Josephine B, Danilo Harles, and Diana Rieger. 2020. “Themen, Motive Und Mainstreaming in Rechtsextremen Online-Memes.” M&K Medien & Kommunikationswissenschaft 68 (1–2): 73–93.

Tufekci, Zeynep. 2018. “YouTube, the Great Radicalizer.” The New York Times, June 8, 2018.https://www.nytimes.com/2018/03/10/opinion/sunday/youtube-politics-radical.html.

Vosoughi, Soroush, Deb Roy, and Sinan Aral. 2018. “The Spread of True and False News Online.” Science 359 (6380): 1146–51.https://doi.org/10.1126/science.aap9559.

Wagner, Anna, and Christian Schwarzenegger. 2020. “A Populism of Lulz: The Proliferation of Humor, Satire, and Memes as Populist Communication in Digital Culture.” In , 313–32. Nomos Verlagsgesellschaft mbH & Co. KG.

Zuckerberg, Mark. 2017. “Bringing the World Closer Together.” Facebook. June 22, 2017.https://www.facebook.com/notes/mark-zuckerberg/bringing-the-world-closer-together/10154944663901634/.