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Taking the lead in misinformation-related conversations in social media networks during a mass shooting crisis.
- Source :
-
Internet Research . 2023, Vol. 33 Issue 2, p638-663. 26p. - Publication Year :
- 2023
-
Abstract
- Purpose: Misinformation (i.e. information identified as false) spreads widely and quickly on social media – a space where crowds of ordinary citizens can become leading voices – during a crisis when information is in short supply. Using the theoretical lenses of socially curated flow and networked gatekeeping frameworks, we address the following three aims: First, we identify emergent opinion leaders in misinformation-related conversations on social media. Second, we explore distinct groups that contribute to online discourses about misinformation. Lastly, we investigate the actual dominance of misinformation within disparate groups in the early phases of mass shooting crises. Design/methodology/approach: This paper used network and cluster analyses of Twitter data that focused on the four most prevalent misinformation themes surrounding the El Paso mass shooting. Findings: A total of seven clusters of users emerged, which were classified into five categories: (1) boundary-spanning hubs, (2) broadly popular individuals, (3) reputation-building hubs, (4) locally popular individuals and (5) non-opinion leaders. Additionally, a content analysis of 128 tweets in six clusters, excluding the cluster of non-opinion leaders, further demonstrated that the opinion leaders heavily focused on reiterating and propagating misinformation (102 out of 128 tweets) and collectively made zero corrective tweets. Originality/value: These findings expand the intellectual understanding of how various types of opinion leaders can shape the flow of (mis)information in a crisis. Importantly, this study provides new insights into the role of trans-boundary opinion leaders in creating an echo chamber of misinformation by serving as bridges between otherwise fragmented discourses. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10662243
- Volume :
- 33
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Internet Research
- Publication Type :
- Academic Journal
- Accession number :
- 163113844
- Full Text :
- https://doi.org/10.1108/INTR-02-2021-0120