Lambretta: Learning to Rank for Twitter Soft Moderation

Paudel, Pujan; Blackburn, Jeremy; Cristofaro, Emiliano De; Zannettou, Savvas; Stringhini, Gianluca

doi:10.1109/sp46215.2023.10179392

Cited by 2 publications

(2 citation statements)

References 92 publications

(104 reference statements)

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“…There is a growing interest in computational social science to research the behavior of fringe communities at Gab (Ali et al 2021;Zannettou et al 2018), 4chan (Hine et al 2017Papasavva et al 2020), Voat (Papasavva et al 2021), BitChute (Trujillo et al 2020), Gettr (Paudel et al 2022), or Parler (Aliapoulios et al 2021;Baines, Ittefaq, and Abwao 2021;Jakubik et al 2023;Munn 2021;Otala et al 2021;Pieroni et al 2021). In this work, we focus on Parler due to its alleged role in inciting violence, disseminating extreme far-right content (Aliapoulios et al 2021;Hitkul et al 2021), and its relevance for hosting conspiracy theories as is the case for QAnon (Aliapoulios et al 2021).…”

Section: Related Workmentioning

confidence: 99%

Finding Qs: Profiling QAnon Supporters on Parler

Bär¹,

Pröllochs²,

Feuerriegel³

2023

ICWSM

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The social media platform "Parler'' has emerged into a prominent fringe community where a significant part of the user base are self-reported supporters of QAnon, a far-right conspiracy theory alleging that a cabal of elites controls global politics. QAnon is considered to have had an influential role in the public discourse during the 2020 U.S. presidential election. However, little is known about QAnon supporters on Parler and what sets them aside from other users. Building up on social identity theory, we aim to profile the characteristics of QAnon supporters on Parler. We analyze a large-scale dataset with more than 600,000 profiles of English-speaking users on Parler. Based on users' profiles, posts, and comments, we then extract a comprehensive set of user features, linguistic features, network features, and content features. This allows us to perform user profiling and understand to what extent these features discriminate between QAnon and non-QAnon supporters on Parler. Our analysis is three-fold: (1) We quantify the number of QAnon supporters on Parler, finding that 34,913 users (5.5% of all users) openly report supporting the conspiracy. (2) We examine differences between QAnon vs. non-QAnon supporters. We find that QAnon supporters differ statistically significantly from non-QAnon supporters across multiple dimensions. For example, they have, on average, a larger number of followers, followees, and posts, and thus have a large impact on the Parler network. (3) We use machine learning to identify which user characteristics discriminate QAnon from non-QAnon supporters. We find that user features, linguistic features, network features, and content features, can - to a large extent - discriminate QAnon vs. non-QAnon supporters on Parler. In particular, we find that user features are highly discriminatory, followed by content features and linguistic features.

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Section: Related Workmentioning

confidence: 99%

Finding Qs: Profiling QAnon Supporters on Parler

Bär¹,

Pröllochs²,

Feuerriegel³

2023

ICWSM

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“…In the past few years, though, and partly due to an increased polarization in political spheres, some platforms have managed to create relatively stable and viable alternatives for ideologically non-mainstream users across the political spectrum and sustain a relatively small, yet strong and loud user base. This growth has been arguably more pronounced in the case of platforms that frame themselves as "free speech" platforms, such as Parler (Ali et al, 2021), Gab (Zannettou et al, 2018), Gettr (Paudel et al, 2021), or BitChute (Trujillo et al, 2020), so much so that they have often been considered synonymous to alt-right, far-right, hate speech, and extremist spaces. This rise in popularity and the relative stability of some of these spaces, particularly Gab, gives space to a new form of alternative social media; one that is ideologically-and commercially-in complete opposition and antagonism to the left-leaning, liberal ideological roots of alternative spaces.…”

Section: Introductionmentioning

confidence: 99%

Politicization and Radicalization of Discourses in the Alt-Tech Ecosystem: A Case Study on Gab Social

Dehghan

Nagappa

2022

Social Media + Society

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With the increasing popularity of some alternative social media platforms, the flow of information has to some extent shifted from the periphery to the core, where problematic discourses are produced, reproduced, and amplified in the alternative ecosystem, to later find their way into mainstream platforms. The non- or less-moderated nature of some alternative platforms provides a suitable space for politicization and radicalization of discourses. In this article, we use a case study of conversations about vaccination on Gab Social—an alternative platform often conceptualized as a far-right platform—to examine this radicalization process through a mixed-methods analysis of over 68,000 vaccination-related posts from before the COVID-19 pandemic until August 2021. The article shows that while antagonistic and conspiratorial thinking was an element of vaccination discourses on Gab even before the pandemic, such conversations became gradually politicized, and expanded far beyond the medical discourse and entered the domain of organizational politics.

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Lambretta: Learning to Rank for Twitter Soft Moderation

Cited by 2 publications

References 92 publications

Finding Qs: Profiling QAnon Supporters on Parler

Finding Qs: Profiling QAnon Supporters on Parler

Politicization and Radicalization of Discourses in the Alt-Tech Ecosystem: A Case Study on Gab Social

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