Election Fraud and Misinformation on Twitter: Author, Cluster, and Message Antecedents
Abstract: This study determined the antecedents of diffusion scope (total audience), speed (number of adopters/time), and shape (broadcast vs. person-to-person transmission) for true vs. fake news about a falsely claimed stolen 2020 US Presidential election across clusters of users that responded to one another's tweets ("user clusters"). We examined 31,128 tweets with links to fake vs. true news by 20,179 users to identify 1,069 user clusters via clustering analysis. We tested whether attributes of authors (experience, followers, following, total tweets), time (date), or tweets (link to fake [vs. true] news, retweets) affected diffusion scope, speed, or shape, across user clusters via multilevel diffusion analysis. These tweets showed no overall diffusion pattern; instead, specific explanatory variables determined their scope, speed, and shape. Compared to true news tweets, fake news tweets started earlier and showed greater broadcast influence (greater diffusion speed), scope, and person-t
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Veröffentlichungsversion
begutachtet (peer reviewed)
In: Media and Communication ; 10 (2022) 2 ; 66-80
- Klassifikation
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Englisch
- Ereignis
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Veröffentlichung
- (wo)
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Mannheim
- (wer)
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SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- (wann)
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2022
- Urheber
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Chiu, Ming Ming
Park, Chong Hyun
Lee, Hyelim
Oh, Yu Won
Kim, Jeong-Nam
- DOI
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10.17645/mac.v10i2.5168
- URN
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urn:nbn:de:101:1-2023090410382482943447
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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25.03.2025, 13:58 MEZ
Datenpartner
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Beteiligte
- Chiu, Ming Ming
- Park, Chong Hyun
- Lee, Hyelim
- Oh, Yu Won
- Kim, Jeong-Nam
- SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
Entstanden
- 2022
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