Monitoring event-driven dynamics on Twitter

A case study in Belarus

Bibliographic Data

ID22229136
AuthorsNatalie M Rice (0000-0002-3118-0302, University of Tennessee at Knoxville), Benjamin D Horne (0000-0002-5779-3019, University of Tennessee at Knoxville), Catherine A Luther (0000-0001-6117-7211, University of Tennessee at Knoxville), Joshua Borycz (0000-0002-1505-148X, Vanderbilt University), Suzanne Allard (0000-0001-9421-3848, University of Tennessee at Knoxville), Damian J Ruck (0000-0001-8678-8852, University of Tennessee at Knoxville), Michael Fitzgerald (0000-0002-2161-3792, University of Tennessee at Knoxville), Oleg Manaev (0000-0002-1517-3997, University of Tennessee at Knoxville), Baukje Prins (0000-0001-5893-2167, University of Tennessee at Knoxville), Maureen Taylor (0000-0002-9420-3591, University of Technology Sydney), R A Bentley (0000-0001-9086-2197, Knoxville College, corresponding author)
Year2022
Volume2
Issue4
Pages36-36
Publication date2022-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSN Social Sciences (JOURNAL)
Journal identifiersISSN: 2662-9283 • E-ISSN: 2662-9283
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s43545-022-00330-x
PMID35434643
OpenAlexW4225688148
LanguageEN
References cited66

Analysts of social media differ in their emphasis on the effects of message content versus social network structure. The balance of these factors may change substantially across time. When a major event occurs, initial independent reactions may give way to more social diffusion of interpretations of the event among different communities, including those committed to disinformation. Here, we explore these dynamics through a case study analysis of the Russian-language Twitter content emerging from Belarus before and after its presidential election of August 9, 2020. From these Russian-language tweets, we extracted a set of topics that characterize the social media data and construct networks to represent the sharing of these topics before and after the election. The case study in Belarus reveals how misinformation can be re-invigorated in discourse through the novelty of a major event. More generally, it suggests how audience networks can shift from influentials dispensing information before an event to a de-centralized sharing of information after it

Computer security · Data science · Disinformation · Homophily · Information cascade · Microblogging · Misinformation · Novelty · Political science · Politics · Presidential election · Social media · Social network analysis · Sociology · World Wide Web · Computer Science · Misinformation and Its Impacts · Opinion Dynamics and Social Influence · Psychology · Social Media and Politics · Social Psychology

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