Currently accepted at: JMIR Infodemiology
Date Submitted: Jan 5, 2026
Open Peer Review Period: Jan 19, 2026 - Mar 16, 2026
Date Accepted: Jul 8, 2026
(closed for review but you can still tweet)
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/90888
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Distortions, Fabrications, and Manipulations: An Annotated Profile of Fact-checked COVID-19 Misinformation in Arabic
ABSTRACT
Background:
The COVID-19 pandemic gave rise to a global “infodemic” in which social media platforms amplified misinformation. Despite high social media adoption rates and heavy reliance on social media for pandemic news in Arab-speaking countries, relatively little is known about the prevalence and characteristics of online Arabic COVID-19 misinformation.
Objective:
To capture and analyze a snapshot of the COVID-19 misinformation ecosystem in Arabic, identifying characteristics and patterns to guide future research and interventions of particular benefit to this linguistic region.
Methods:
We compiled a database of 234 COVID-19 misinformation claims published online from March 2020 to March 2022, sourced from four International Fact-Checking Network (IFCN)-certified Arabic fact-checking organizations. Claims were coded inductively and deductively with high inter-rater reliability, to determine misinformation type (κ = 0.88), narrative typology (κ = 0.913), framing strategies (κ = 0.72), medical jargon usage (κ = 0.794), and societal implications (κ = 0.752). All Cohen's kappa coefficients were significant at p < 0.001.
Results:
Facebook was the most popular platform, followed by Twitter, with regular users being the primary source of debunked claims. The most prevalent narrative typologies were COVID-19 biological aspects (origins, existence, diagnosis, prevention, transmission, and cures) (47.2%) and vaccines (30%). Fabricated/manipulated (54.9%), followed by misleading content (36.9%), were the most common misinformation types. The most frequent framing strategy involved distortion of science and medicine (29.6%), followed by entertainment/satire (23.6%), political content (18.9%), and conspiracies (13.3%). Notably, 36.3% of claims were translated from English, and only 50% of the analyzed content was moderated by the original platforms.
Conclusions:
Fact-checked Arabic COVID-19 misinformation exhibited distinct patterns, including heavy reliance on translated content, manipulated content, and scientific distortion as a credibility strategy, and significant gaps in platform moderation. These findings highlight the need for enhanced Arabic-language content moderation, cross-linguistic fact-checking collaboration, culturally appropriate media and health literacy interventions, and rebuilding institutional trust to address misinformation in the Arab-world effectively. Clinical Trial: N/A
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.