Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287063 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Business Economics [ISSN:] 1861-8928 [Volume:] 91 [Issue:] 9 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 1299-1329
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Social media networks (SMN) such as Facebook and Twitter are infamous for facilitating the spread of potentially false rumors. Although it has been argued that SMN enable their users to identify and challenge false rumors through collective efforts to make sense of unverified information—a process typically referred to as self-correction—evidence suggests that users frequently fail to distinguish among rumors before they have been resolved. How users evaluate the veracity of a rumor can depend on the appraisals of others who participate in a conversation. Affordances such as the searchability of SMN, which enables users to learn about a rumor through dedicated search and query features rather than relying on interactions with their relational connections, might therefore affect the veracity judgments at which they arrive. This paper uses agent-based simulations to illustrate that searchability can hinder actors seeking to evaluate the trustworthiness of a rumor's source and hence impede self-correction. The findings indicate that exchanges between related users can increase the likelihood that trustworthy agents transmit rumor messages, which can promote the propagation of useful information and corrective posts.
Subjects: 
Affordances
Agent-based simulation and modelling
Sense-making
Social influence
Social media
Social networks
JEL: 
C63
D79
D83
D85
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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