Examining Factors Associated with Twitter Account Suspension Following the 2020 U.S. Presidential Election

Chowdhury, Farhan Asif; Saha, Dheeman; Hasan, Md Rashidul; Saha, Koustuv; Mueen, Abdullah

doi:10.48550/arxiv.2101.09575

Cited by 3 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

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

Toraman,

Şahinuç,

Yilmaz

2021

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Deleted and Suspended Usersmentioning

confidence: 99%

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

Toraman,

Şahinuç,

Yilmaz

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Much of the mis-and disinformation about the election spread online on social media websites like Twitter and Facebook. While platforms introduced new "civic integrity" policies (Chowdhury et al 2021;Niker and Yarrow 2021;EIP 2020a), and enacted enforcement strategies including the application of credibility labels and other mitigation techniques, these actions were not enough to stop false and misleading claims from spreading. In the lead up to the election, and again after January 6, platforms suspended and otherwise sanctioned large numbers of accounts-eventually taking action against then-President Trump's accounts.…”

mentioning

confidence: 99%

Repeat Spreaders and Election Delegitimization

Kennedy

Wack

Beers

et al. 2022

JQD

View full text Add to dashboard Cite

This paper introduces and presents a first analysis of a uniquely curated dataset of misinformation, disinformation, and rumors spreading on Twitter about the 2020 U.S. election. Previous research on misinformation—an umbrella term for false and misleading content—has largely focused either on broad categories, using a finite set of keywords to cover a complex topic, or on a few, focused case studies, with increased precision but limited scope. Our approach, by comparison, leverages real-time reports collected from September through November 2020 to develop a comprehensive dataset of tweets connected to 456 distinct misinformation stories from the 2020 U.S. election (our ElectionMisinfo2020 dataset), 307 of which sowed doubt in the legitimacy of the election. By relying on real-time incidents and streaming data, we generate a curated dataset that not only provides more granularity than a large collection based on a finite number of search terms, but also an improved opportunity for generalization compared to a small set of case studies. Though the emphasis is on misleading content, not all of the tweets linked to a misinformation story are false: some are questions, opinions, corrections, or factual content that nonetheless contributes to misperceptions. Along with a detailed description of the data, this paper provides an analysis of a critical subset of election-delegitimizing misinformation in terms of size, content, temporal diffusion, and partisanship. We label key ideological clusters of accounts within interaction networks, describe common misinformation narratives, and identify those accounts which repeatedly spread misinformation. We document the asymmetry of misinformation spread: accounts associated with support for President Biden shared stories in ElectionMisinfo2020 far less than accounts supporting his opponent. That asymmetry remained among the accounts who were repeatedly influential in the spread of misleading content that sowed doubt in the election: all but two of the top 100 ‘repeat spreader’ accounts were supporters of then-President Trump. These findings support the implementation and enforcement of ‘strike rules’ on social media platforms, directly addressing the outsized role of repeat spreaders.

show abstract

Repeat Spreaders and Election Delegitimization: A Comprehensive Dataset of Misinformation Tweets from the 2020 U.S. Election

Kennedy¹,

Wack²,

Beers³

et al. 2022

Preprint

View full text Add to dashboard Cite

This paper introduces and presents a first analysis of a uniquely curated dataset of misinformation, disinformation, and rumors spreading on Twitter about the 2020 U.S. Election. Previous research on misinformation — an umbrella term for false and misleading content — has largely focused either on broad categories, using a finite set of keywords to cover a complex topic, or on a few, focused case studies, with increased precision but limited scope. Our approach, by comparison, leverages real-time reports collected from September through November 2020 to develop a comprehensive dataset of tweets connected to 456 distinct misinformation stories from the 2020 US Presidential election (our ElectionMisinfo2020 dataset), 307 of which sowed doubt in the legitimacy of the election. By relying on real-time incidents and streaming data, we generate a curated dataset that not only provides more granularity than a large collection based on a finite number of search terms, but also an improved opportunity for generalization compared to a small set of case studies. Though the emphasis is on misleading content, not all of the tweets linked to a misinformation story are false: some are questions, opinions, corrections, or factual content that nonetheless contributes to misperceptions. Along with a detailed description of the data, this paper provides an analysis of a critical subset of election-delegitimizing misinformation in terms of size, content, temporal diffusion, and partisanship. We label key ideological clusters of accounts within interaction networks, describe common misinformation narratives, and identify those accounts which repeatedly spread misinformation. We document the asymmetry of misinformation spread: accounts associated with support for President Biden shared stories in ElectionMisinfo2020 far less than accounts supporting his opponent. That asymmetry remained among the accounts who were repeatedly influential in the spread of misleading content that sowed doubt in the election: all but two of the top 100 ‘repeat spreader’ accounts were supporters of then-President Trump. These findings support the implementation and enforcement of ‘strike rules’ on social media platforms, directly addressing the outsized role of repeat spreaders.

show abstract

Examining Factors Associated with Twitter Account Suspension Following the 2020 U.S. Presidential Election

Cited by 3 publications

References 0 publications

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

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

Repeat Spreaders and Election Delegitimization

Repeat Spreaders and Election Delegitimization: A Comprehensive Dataset of Misinformation Tweets from the 2020 U.S. Election

Contact Info

Product

Resources

About