From pandemic to Plandemic : Examining the amplification and attenuation of COVID-19 misinformation on social media

Copyright © 2023 Elsevier Ltd. All rights reserved..

This study examines the proliferation of COVID-19 misinformation through Plandemic-a pseudo-documentary of COVID-19 conspiracy theories-on social media and examines how factors such as (a) themes of misinformation, (b) types of misinformation, (c) sources of misinformation, (d) emotions of misinformation, and (e) fact-checking labels amplify or attenuate online misinformation during the early days of the pandemic. Using CrowdTangle, a Facebook API, we collected a total of 5732 publicly available Facebook pages posts containing Plandemic-related keywords from January 1 to December 19, 2020. A random sample of 600 posts was subsequently coded, and the data were analyzed using negative binomial regression to examine factors associated with amplification and attenuation. Overall, the extended an extended Social Amplification of Risk Framework (SARF) provided a theoretical lens to understand why certain misinformation was amplified, while others were attenuated. As for posts with misinformation, results showed that themes related to private firms, treatment and prevention of virus transmission, diagnosis and health impacts, virus origins, and social impact were more likely to be amplified. While the different types of misinformation (manipulated, fabricated, or satire) and emotions were not associated with amplification, the type of fact-check labels did influence the virality of misinformation. Specifically, posts that were flagged as false by Facebook were more likely to be amplified, while the virality of posts flagged as containing partially false information was attenuated. Theoretical and practical implications were discussed.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:328

Enthalten in:

Social science & medicine (1982) - 328(2023) vom: 01. Juli, Seite 115979

Sprache:

Englisch

Beteiligte Personen:

Lee, Edmund W J [VerfasserIn]
Bao, Huanyu [VerfasserIn]
Wang, Yixi [VerfasserIn]
Lim, Yi Torng [VerfasserIn]

Links:

Volltext

Themen:

Big data
COVID-19
Journal Article
Misinformation
Pandemic
Research Support, Non-U.S. Gov't
Social amplification of risk
Social media

Anmerkungen:

Date Completed 16.06.2023

Date Revised 20.06.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.socscimed.2023.115979

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM357474783