On Twitter Purge: A Retrospective Analysis of Suspended Users

Chowdhury, Farhan Asif; Allen, Lawrence R.; Yousuf, Mohammad; Mueen, Abdullah

doi:10.1145/3366424.3383298

Cited by 19 publications

(21 citation statements)

References 21 publications

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“…However, both Suspended and Control users have similar friends count (t=-6.74, p<0.05). These findings resonate with previous works studying spamming and suspension on Twitter (Thomas et al 2011;Chowdhury et al 2020), which identified that the rules violating users are generally short-lived, posts more tweet, and have a smaller follower base.…”

Section: Rq1: Inferring Suspension Reasonsupporting

confidence: 91%

“…There have been several works related to Twitter suspension, most of which focused primarily on spam-related suspensions (Thomas et al 2011;Amleshwaram et al 2021) (Chowdhury et al 2020). We refer readers to (Le et al 2019;Chowdhury et al 2020) for a more comprehensive understanding of suspension and moderation on online platforms. However, none of these works quantify specific factors associated with Twitter suspension.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

Chowdhury¹,

Saha²,

Hasan³

et al. 2021

Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

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Online social media enables mass-level, transparent, and democratized discussion on numerous socio-political issues. Due to such openness, these platforms often endure manipulation and misinformation -leading to negative impacts. To prevent such harmful activities, platform moderators employ countermeasures to safeguard against actors violating their rules. However, the correlation between publicly outlined policies and employed action is less clear to general people. In this work, we examine violations and subsequent moderations related to the 2020 U.S. President Election discussion on Twitter. We focus on quantifying plausible reasons for the suspension, drawing on Twitter's rules and policies by identifying suspended users (Case) and comparing their activities and properties with (yet) non-suspended (Control ) users. Using a dataset of 240M election-related tweets made by 21M unique users, we observe that Suspended users violate Twitter's rules at a higher rate (statistically significant) than Control users across all the considered aspects -hate speech, offensiveness, spamming, and civic integrity. Moreover, through the lens of Twitter's suspension mechanism, we qualitatively examine the targeted topics for manipulation.

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Section: Rq1: Inferring Suspension Reasonsupporting

confidence: 91%

Section: Related Workmentioning

confidence: 99%

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

Chowdhury¹,

Saha²,

Hasan³

et al. 2021

Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Self Cite

View full text Add to dashboard Cite

show abstract

“…Also, Darwish [13] study 23M tweets related to the US Supreme Court judge Brett Kavanaugh, finding that the hashtags #QAnon and #WWG1WGA 2 are in the top six in their dataset. Chowdhury et al [12] collect 1M tweets from 2.4M suspended Twitter accounts, finding that politically motivated users consistently spread conspiracies including QAnon. Finally, [48] studies "follow trains" (long lists of like-minded accounts that are mentioned for others to follow) on 5.5K Twitter accounts aiming to analyze political echo-chambers, finding that Republican users tweet QAnon-related hashtags often.…”

Section: Related Workmentioning

confidence: 99%

The Gospel According to Q: Understanding the QAnon Conspiracy from the Perspective of Canonical Information

Papasavva¹,

Aliapoulios²,

Ballard³

et al. 2021

Preprint

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The QAnon conspiracy theory claims that a cabal of (literally) blood thirsty politicians and media personalities are engaged in a war to destroy society. By interpreting cryptic "drops" of information from an anonymous insider calling themselves Q, adherents of the conspiracy theory believe that they are being led by Donald Trump in an active fight against this cabal. QAnon has been covered extensively by the media, as its adherents have been involved in multiple violent acts, including the January 6th, 2021 seditious storming of the US Capitol building. Nevertheless, we still have relatively little understanding of how the theory evolved and was spread on the Web, and the role played in that by multiple platforms.To address this gap, in this paper we study QAnon from the perspective of "Q" themself. Specifically, we build a dataset of 4,949 canonical Q drops collected from six "aggregation sites," which curate and archive them from their original posting to anonymous and ephemeral image boards. We expose that these sites have relatively low (overall) agreement, and thus at least some Q drops should probably be considered apocryphal. We then analyze the contents of the Q drops themselves, identifying topics of discussion, as well as finding statistically significant indications that drops were not authored by a single individual. Finally, we look at how posts on Reddit are used to disseminate Q drops to a wider audience. We find that dissemination was (originally) limited to a few sub-communities and that, while heavy-handed content moderation decisions have reduced the overall issue, the "gospel" of Q persists on Web communities.

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“…The factors behind social media suspension are analyzed in different cases rather than the 2020 BlackLivesMatter movement [33,21,12,13]. Similarly, there are studies to understand the reasons for why users delete their social media accounts [2,41,7].…”

Section: Deleted and Suspended Usersmentioning

confidence: 99%

“…Social media is a tool for people discussing and sharing opinions, as well as getting information and news. A recent study shows that 71% of Twitter users get news from this platform [27], which emphasizes the threat of fake news [16] and misinformation spread [12,34]. After George Floyd's death in May 2020, the volume of discussion in social media increased dramatically.…”

Section: Introductionmentioning

confidence: 99%

BlackLivesMatter 2020: An Analysis of Deleted and Suspended Users in Twitter

Toraman,

Şahinuç,

Yilmaz

2021

Preprint

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After George Floyd's death in May 2020, the volume of discussion in social media increased dramatically. A series of protests followed this tragic event, called as the 2020 BlackLivesMatter (BLM) movement. People participated in the discussion for several reasons; including protesting and advocacy, as well as spamming and misinformation spread. Eventually, many user accounts are deleted by their owners or suspended due to violating the rules of social media platforms. In this study, we analyze what happened in Twitter before and after the event triggers. We create a novel dataset that includes approximately 500k users sharing 20m tweets, half of whom actively participated in the 2020 BLM discussion, but some of them were deleted or suspended later. We have the following research questions: What differences exist (i) between the users who did participate and not participate in the BLM discussion, and (ii) between old and new users who participated in the discussion? And, (iii) why are users deleted and suspended? To find answers, we conduct several experiments supported by statistical tests; including lexical analysis, spamming, negative language, hate speech, and misinformation spread.

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On Twitter Purge: A Retrospective Analysis of Suspended Users

Cited by 19 publications

References 21 publications

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

The Gospel According to Q: Understanding the QAnon Conspiracy from the Perspective of Canonical Information

BlackLivesMatter 2020: An Analysis of Deleted and Suspended Users in Twitter

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