Online hate network spreads malicious COVID-19 content outside the control of individual social media platforms

Abstract

We show that malicious COVID-19 content, including racism, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond the control of any individual social media platform. We provide a first mapping of the online hate network across six major social media platforms. We demonstrate how malicious content can travel across this network in ways that subvert platform moderation efforts. Machine learning topic analysis shows quantitatively how online hate communities are sharpening COVID-19 as a weapon, with topics evolving rapidly and content becoming increasingly coherent. Based on mathematical modeling, we provide predictions of how changes to content moderation policies can slow the spread of malicious content.

Connectivity Between Russian Information Sources and Extremist Communities Across Social Media Platforms

“…Our methodological approach to building the map of the social media platforms' communities and their interconnectionsand classifying their content-is exactly the same as that in Johnson et al, 2019, Velásquez et al (2021 where it is laid out in detail with examples. Summarizing, it involves identifying clusters that satisfy the criteria that we set, then collecting the links between them.…”

“…In addition, all in-built communities can feature links into other communities whose content is of interest to them, within the same-and also across different-social media platforms. Again, extremist communities are no different, and typically do this a lot across platforms in order to keep their members away from moderator pressure (Johnson et al, 2019;Velásquez et al, 2021). The net result is a highly complex, interconnected ecosystem of communities within and across platforms, together with links into external information sources of various kinds.…”

“…In what follows, we refer to each such online community (e.g., Facebook Page, Telegram Channel) as a "cluster" in order to avoid confusion with platform-specific definitions and network discovery algorithms. Our choice of the word "cluster" is exactly as in previous published work (Johnson et al, 2019;Velásquez et al, 2021). For example, it avoids any possible confusion with the term "community" in network science which has the different meaning of a subnetwork that is inferred from a specific partitioning algorithm and hence is algorithm dependent.…”

“…VKontakte was banned in Ukraine in 2017 in an attempt to stem Russian disinformation, yet it persisted as the country's 4th most popular site. The smaller platforms 4chan, Gab and Telegram add to this mix, with their users' many links to each other and to the larger platforms helping to entangle the ecosystem more tightly (Johnson et al, 2019;Velásquez et al, 2021). Moreover, they tend to be more lenient toward hate speech and conspiracy theories (McLaughlin, 2019).…”

Covid-19 vaccines production and societal immunization under the serendipity-mindsponge-3D knowledge management theory and conceptual framework

“…Some people believed in the conspiracy theory that Covid-19 was spread by 5G wireless towers, resulting in around 80 harassment incidents, 30 acts of arson and vandalism, and even burning cell towers [23]. Covid-19-related information was also used as a weapon by online hate communities, such as neo-Nazis, fascists, white supremacists, anti-Semites, Islamophobes, cis-gender male supremacists, to push ideas of malicious intents [24].…”