How social media shapes polarization

Bavel, Jay Joseph Van; Rathje, Steve; Harris, Elizabeth; Robertson, Claire; Sternisko, Anni

doi:10.1016/j.tics.2021.07.013

Cited by 101 publications

(54 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This is possible for some of the well-known multi-valued or binary attributes. However, in ever-increasing polarized social networks [ 44 , 45 ] with a wide variety of discourses, discussion topics, and trends, the realization of conflicting attributes is not feasible. Our main idea is to find users with an arbitrary and somewhat unique set of attributes in the entire network and label them as suspected for further investigations.…”

Section: The Proposed Approachmentioning

confidence: 99%

Detection of fickle trolls in large-scale online social networks

Shafiei

Dadlani

2022

J Big Data

View full text Add to dashboard Cite

Online social networks have attracted billions of active users over the past decade. These systems play an integral role in the everyday life of many people around the world. As such, these platforms are also attractive for misinformation, hoaxes, and fake news campaigns which usually utilize social trolls and/or social bots for propagation. Detection of so-called social trolls in these platforms is challenging due to their large scale and dynamic nature where users’ data are generated and collected at the scale of multi-billion records per hour. In this paper, we focus on fickle trolls, i.e., a special type of trolling activity in which the trolls change their identity frequently to maximize their social relations. This kind of trolling activity may become irritating for the users and also may pose a serious threat to their privacy. To the best of our knowledge, this is the first work that introduces mechanisms to detect these trolls. In particular, we discuss and analyze troll detection mechanisms on different scales. We prove that the order of centralized single-machine detection algorithm is $$O(n^3)$$ O ( n 3 ) which is slow and impractical for early troll detection in large-scale social platforms comprising of billions of users. We also prove that the streaming approach where data is gradually fed to the system is not practical in many real-world scenarios. In light of such shortcomings, we then propose a massively parallel detection approach. Rigorous evaluations confirm that our proposed method is at least six times faster compared to conventional parallel approaches.

show abstract

Section: The Proposed Approachmentioning

confidence: 99%

Detection of fickle trolls in large-scale online social networks

Shafiei

Dadlani

2022

J Big Data

View full text Add to dashboard Cite

show abstract

“…While a full discussion of the role of the media is beyond the scope of this article (see Van Swol et al, 2022), we briefly highlight research on the potential impact of social media on polarization, particularly as it relates to a breakdown of intergroup contact and dialogue. To be sure, there remains debate about the extent of the impact of social media on polarization (e.g., Van Bavel et al, 2021), but there appears to be some consensus that it does, indeed, play a role (Barrett et al, 2021; Van Bavel et al, 2021).…”

Section: The Impact Of (Social) Mediamentioning

confidence: 99%

“…Interestingly, reviews of the empirical research on social media and political polarization conclude that, while social media does play a role in polarization, it may not be the primary driver of it. For example, Van Bavel et al (2021) suggested that, while a popular notion is that social media creates “echo chambers” of like-minded individuals and thus furthers division, “the number of Americans who consume highly polarized content online is dwarfed by the number who consume more centrist media, or the number of Americans who simply do not care about politics” (p. 913). The finding that social media is not the primary driver of political polarization is also supported by a recent report by the NYU Stern Center for Business and Human Rights (Barrett et al, 2021).…”

Section: The Impact Of (Social) Mediamentioning

confidence: 99%

A breakdown (and rebuilding) of intergroup dialogue.

Miles¹,

Shinew²

2022

Group Dynamics: Theory, Research, and Practice

View full text Add to dashboard Cite

Objective: We argue the January 6th, 2021, insurrection represents the culmination of a breakdown of intergroup dialogue in the U.S. We further argue that group psychologists and group psychotherapists can help us understand the antecedents and outcomes of this breakdown and provide a productive way forward through fostering and facilitating intergroup dialogue and researching the process and outcomes of this small group intervention. Method: We review research related to some of the antecedents of a breakdown of dialogue across groups in the U.S. (e.g., affective polarization and social media) to highlight a need for more meaningful intergroup contact that reduces political and other identity-based (e.g., racial) segregation and builds intergroup understanding and empathy. Results: We illustrate how intergroup dialogue, a small group intervention, can help begin to address some of the antecedents and consequences of the breakdown in dialogue that preceded the insurrection on a local level. Conclusion: We conclude that group psychologists and group psychotherapists should devote efforts to understanding the process and outcomes of difficult intergroup dialogues (including how to increase participation in these dialogues), and use their group work skills to facilitate these dialogues on a local level.

show abstract

“…Attention to social media is also a key driver of beliefs in misinformation (Uscinski 2020) in part because social media makes spreads it easily (Yee 2020) and because it increases party loyalty over truth (Bavel et al 2018), shaping political polarization through selective partisanship and content mechanisms (Van Bavel et al 2021). The rapid flow of information on the Internet allows for immediate refutation (or shaming) of conspiracy thinking (Clarke 2007).…”

Section: Introductionmentioning

confidence: 99%

Conspiratorial thinking in the Latino community on the 2020 election

Cortina

Rottinghaus

2022

Research & Politics

View full text Add to dashboard Cite

Political knowledge is the cornerstone of a functional representative democracy, but belief in conspiracy theories disrupts that connection and may be dangerous with consequences for democracy. Pundits and politicians have speculated about the cause and effect of misinformation and conspiracy theories, but no work has examined what causes beliefs in conspiracy theories or misinformation among Latinos specifically. In a unique survey of Texas Latinos prior to the 2020 election, we find belief in conspiracy theories is most related to support for Donald Trump and greater reliance on Spanish-language media and social media. The results highlight how conspiratorial thinking manifests in specific ethnic groups and the need to counter those beliefs in Spanish-language media.

show abstract

How social media shapes polarization

Cited by 101 publications

References 16 publications

Detection of fickle trolls in large-scale online social networks

Detection of fickle trolls in large-scale online social networks

A breakdown (and rebuilding) of intergroup dialogue.

Conspiratorial thinking in the Latino community on the 2020 election

Contact Info

Product

Resources

About