Hey nettimers, Some on the list might be interested in contributing to this issue I'll be proposing to Big Data & Society.
Description below or a PDF if preferred here ( https://pdfhost.io/v/NrRIuypHM_Divisive_Datapdf.pdf). Flick me a title and abstract by August 17 if you're keen. best, Luke Divisive Data [ Context: Big Data & Society has issued a call for Special Theme Proposals, due September 15, 2020. 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, which can be submitted 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), pipe bombs (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.m...@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. # distributed via <nettime>: no commercial use without permission # <nettime> is a moderated mailing list for net criticism, # collaborative text filtering and cultural politics of the nets # more info: http://mx.kein.org/mailman/listinfo/nettime-l # archive: http://www.nettime.org contact: nett...@kein.org # @nettime_bot tweets mail w/ sender unless #ANON is in Subject:
