Options
Diffusion and persistence of false rumors in social media networks: implications of searchability on rumor self-correction on Twitter
Eismann, Kathrin (2021): Diffusion and persistence of false rumors in social media networks: implications of searchability on rumor self-correction on Twitter, in: Journal of Business Economics, Berlin ; Heidelberg: Springer, Jg. 91, Nr. 9, S. 1299–1329, doi: 10.1007/s11573-020-01022-9.
Faculty/Chair:
Author:
Title of the Journal:
Journal of Business Economics
ISSN:
0044-2372
1861-8928
Publisher Information:
Year of publication:
2021
Volume:
91
Issue:
9
Pages:
Language:
English
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.
GND Keywords: ; ; ;
Agent <Künstliche Intelligenz>
Computersimulation
Social Media
Soziales Netzwerk
Keywords: ; ; ; ; ;
Affordances
Agent-based simulation and modelling
Sense-making
Social influence
Social media
Social networks
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Article
Activation date:
February 16, 2021
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/49505