Elites and foreign actors among the alt-right: The Gab social media platform

Abstract

Content regulation and censorship of social media platforms is increasingly discussed by governments and the platforms themselves. To date, there has been little data-driven analysis of the effects of regulated content deemed inappropriate on online user behavior. We therefore compared Twitter — a popular social media platform that occasionally removes content in violation of its Terms of Service — to Gab — a platform that markets itself as completely unregulated. Launched in mid-2016, Gab is, in practice, dominated by individuals who associate with the “alt-right” political movement in the United States. Despite its billing as “The Free Speech Social Network,” Gab users display more extreme social hierarchy and elitism when compared to Twitter. Although the framing of the site welcomes all people, Gab users’ content is more homogeneous, preferentially sharing material from sites traditionally associated with the extremes of American political discourse, especially the far right. Furthermore, many of these sites are associated with state-sponsored propaganda from foreign governments. Finally, we discovered a significant presence of German language posts on Gab, with several topics focusing on German domestic politics, yet sharing significant amounts of content from U.S. and Russian sources. These results indicate possible emergent linkages between domestic politics in European and American far right political movements. Implications for regulation of social media platforms are discussed.

#Election2020: the first public Twitter dataset on the 2020 US Presidential election

“…As a result, we are releasing a collection of Tweet IDs that researchers are then able to use in tandem with Twitter's API to retrieve the full tweet payload. We recommend using tools such as DocNow's Hydrator 17 or Twarc 18 ; if tweets have been deleted from Twitter's platform, researchers will be unable to retrieve the payloads for those tweets. We provide ready-to-use Python code scripts to perform all the operations described above in our repository.…”

Hate Contagion: Measuring the spread and trajectory of hate on social media

“…Gab is known for its lax hate speech moderation policies and the high proportion of messages containing explicit hate terms (Lima et al, 2018;Zannettou et al, 2018), and is seen as 'rolling out the welcome mat' to users banned from social media sites (Anti-Defamation League, 2019). The platform is heavily focused on political content and topics closely follow current affairs, particularly around political ideology, race, and terrorism (Zhou, Dredze, Broniatowski, & Adler, 2019), including Nazi imagery, antisemitic material, holocaust denial, islamophobia, along with much wider forms of hate against other target groups (Weich, 2019). In addition, the platform has been used as a recruitment tool by several neo-Nazi and alt-right groups (Katz, 2018), and the rise in popularity of extremist far-right groups on Gab has been suggested to be "remarkably similar" to the rise of ISIS on mainstream social media in prior years (Makuch, 2019).…”

Mutual radicalisation of opposing extremist groups via the Internet

“…It has since returned in a distributed format, making it even less resistant to moderation, and is more popular than ever (Gilbert, 2019;Tech Against Terrorism, 2019). The platform is heavily focused on political content and topics closely follow current affairs, particularly around ideology, race, and terrorism (Zhou, Dredze, Broniatowski, & Adler, 2019).…”

“…Instead, given that our hate speech classifier was trained on English language content and will therefore not have performed for German language messages, we have not detected German users exposure to hate speech messages in German but only in English, which likely only represents a small proportion. Additionally, while Germany is the third most common country of origin for Gab users (Zannettou et al, 2018), it trails the USA and UK substantially, with only 5% of accounts belonging to German users (Zhou et al, 2019) compared to 88% from the USA or UK. This means that the sample may simply be too small to detect a relationship, and that much meaningful German fringe far-right conversations are occurring elsewhere (Guhl, Ebner, & Rau, 2020).…”

“…This means that the sample may simply be too small to detect a relationship, and that much meaningful German fringe far-right conversations are occurring elsewhere (Guhl, Ebner, & Rau, 2020). Finally, there may be high levels of inauthentic accounts or automated activity for German accounts on Gab (Zhou et al, 2019). In future, developing cross-language hate speech detection approaches would bring additional insight into international variation in these relationships (Vidgen & Derczynski, 2020).…”