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Adherence to Misinformation on Social Media Through Socio-Cognitive and Group-Based Processes

Efstratiou, Alexandros; Cristofaro, Emiliano De; (2022) Adherence to Misinformation on Social Media Through Socio-Cognitive and Group-Based Processes. In: Proceedings of the 25th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2022). Association for Computing Machinery (ACM) (In press). Green open access

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Abstract

Previous work suggests that people's preference for different kinds of information depends on more than just accuracy. This could happen because the messages contained within different pieces of information may either be well-liked or repulsive. Whereas factual information must often convey uncomfortable truths, misinformation can have little regard for veracity and leverage psychological processes which increase its attractiveness and proliferation on social media. In this review, we argue that when misinformation proliferates, this happens because the social media environment enables adherence to misinformation by reducing, rather than increasing, the psychological cost of doing so. We cover how attention may often be shifted away from accuracy and towards other goals, how social and individual cognition is affected by misinformation and the cases under which debunking it is most effective, and how the formation of online groups affects information consumption patterns, often leading to more polarization and radicalization. Throughout, we make the case that polarization and misinformation adherence are closely tied. We identify ways in which the psychological cost of adhering to misinformation can be increased when designing anti-misinformation interventions or resilient affordances, and we outline open research questions that the CSCW community can take up in further understanding this cost.

Type: Proceedings paper
Title: Adherence to Misinformation on Social Media Through Socio-Cognitive and Group-Based Processes
Event: 25th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2022)
Open access status: An open access version is available from UCL Discovery
Publisher version: https://cscw.acm.org/2022/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10151281
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