Conspiracy Theories in the Middle Ages and the Early Modern Period

Zwierlein, Cornel

doi:10.4324/9780429452734-5_2

Cited by 4 publications

(2 citation statements)

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“…A llegations of malign acts, carried out in secret by powerful groups, have been offered as explanations for major events throughout history, from ancient Rome, through the medieval period, to the present day (Brotherton, 2015;Pagán, 2020;Zwierlein, 2020). People across the globe have shared these conspiracy theories (Butter & Knight, 2020;West & Sanders, 2003).…”

Section: Introductionmentioning

confidence: 99%

Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election

Youngblood,

Stubbersfield,

Morin

et al. 2023

Humanit Soc Sci Commun

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During the 2020 US presidential election, conspiracy theories about large-scale voter fraud were widely circulated on social media platforms. Given their scale, persistence, and impact, it is critically important to understand the mechanisms that caused these theories to spread. The aim of this preregistered study was to investigate whether retweet frequencies among proponents of voter fraud conspiracy theories on Twitter during the 2020 US election are consistent with frequency bias and/or content bias. To do this, we conducted generative inference using an agent-based model of cultural transmission on Twitter and the VoterFraud2020 dataset. The results show that the observed retweet distribution is consistent with a strong content bias causing users to preferentially retweet tweets with negative emotional valence. Frequency information appears to be largely irrelevant to future retweet count. Follower count strongly predicts retweet count in a simpler linear model but does not appear to drive the overall retweet distribution after temporal dynamics are accounted for. Future studies could apply our methodology in a comparative framework to assess whether content bias for emotional valence in conspiracy theory messages differs from other forms of information on social media.

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Section: Introductionmentioning

confidence: 99%

Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election

Youngblood,

Stubbersfield,

Morin

et al. 2023

Humanit Soc Sci Commun

View full text Add to dashboard Cite

show abstract

“…Allegations of malign acts, carried out in secret by powerful groups, have been offered as explanations for major events throughout history, from ancient Rome, through the medieval period, to the present day (Brotherton, 2015;Pagán, 2020;Zwierlein, 2020). People across the globe have shared these conspiracy theories (Butter & Knight, 2020;West & Sanders, 2003).…”

Section: Introductionmentioning

confidence: 99%

Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election

Youngblood¹,

Acerbi²,

Glassman³

et al. 2021

Preprint

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During the 2020 US presidential election, conspiracy theories about large-scale voter fraud were widely circulated on social media platforms. Given their scale, persistence, and impact, it is critically important to understand the mechanisms that caused these theories to spread so rapidly. The aim of this study was to investigate whether retweet frequencies among proponents of voter fraud conspiracy theories on Twitter during the 2020 US election are consistent with frequency bias, demonstrator bias, and/or content bias. To do this, we conducted generative inference using an agent-based model of cultural transmission on Twitter and the VoterFraud2020 dataset. The results show that the observed retweet distribution is consistent with a strong content bias and demonstrator bias, likely targeted towards negative emotion and follower count, respectively. Based on the confounding effects of the timeline algorithm and population structure, we are most confident in concluding that the differential spread of voter fraud claims among proponents of voter fraud conspiracy theories on Twitter during and after the 2020 US election was partly driven by a content bias causing users to preferentially retweet tweets with more negative emotion.

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2022

Studies in European Urban History (1100-1800)

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Conspiracy Theories in the Middle Ages and the Early Modern Period

Cited by 4 publications

References 0 publications

Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election

Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election

Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election

Back Matter ("Bibliography", "Index")

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