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Characterizing and Comparing COVID-19 Misinformation Across Languages, Countries and Platforms

Authors:

Golshan Madraki,

Isabella Grasso,

Jacqueline M. Otala,

Jeanna MatthewsAuthors Info & Claims

WWW '21: Companion Proceedings of the Web Conference 2021

Pages 213 - 223

https://doi.org/10.1145/3442442.3452304

Published: 03 June 2021 Publication History

Abstract

Misinformation/disinformation about COVID-19 has been rampant on social media around the world. In this study, we investigate COVID-19 misinformation/ disinformation on social media in multiple languages/countries: Chinese (Mandarin)/China, English/USA, and Farsi (Persian)/Iran; and on multiple platforms such as Twitter, Facebook, Instagram, WhatsApp, Weibo, WeChat and TikTok. Misinformation, especially about a global pandemic, is a global problem yet it is common for studies of COVID-19 misinformation on social media to focus on a single language, like English, a single country, like the USA, or a single platform, like Twitter. We utilized opportunistic sampling to compile 200 specific items of viral and yet debunked misinformation across these languages, countries and platforms emerged between January 1 and August 31. We then categorized this collection based both on the topics of the misinformation and the underlying roots of that misinformation. Our multi-cultural and multi-linguistic team observed that the nature of COVID-19 misinformation on social media varied in substantial ways across different languages/countries depending on the cultures, beliefs/religions, popularity of social media, types of platforms, freedom of speech and the power of people versus governments. We observe that politics is at the root of most of the collected misinformation across all three languages in this dataset. We further observe the different impact of government restrictions on platforms and platform restrictions on content in China, Iran, and the USA and their impact on a key question of our age: how do we control misinformation without silencing the voices we need to hold governments accountable?

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Efstratiou AEfstratiou MYudhoatmojo SBlackburn JDe Cristofaro E(2024)"Here's Your Evidence": False Consensus in Public Twitter Discussions of COVID-19 ScienceProceedings of the ACM on Human-Computer Interaction10.1145/36870108:CSCW2(1-33)Online publication date: 8-Nov-2024
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cover image ACM Conferences

WWW '21: Companion Proceedings of the Web Conference 2021

April 2021

726 pages

ISBN:9781450383134

DOI:10.1145/3442442

Editors:
Jure Leskovec
Stanford
,
Marko Grobelnik
Jožef Stefan Institute
,
Marc Najork
Google
,
Jie Tang
Tsinghua University
,
Leila Zia
Wikimedia Foundation

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Published: 03 June 2021

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Cited By

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https://doi.org/10.1177/20563051241269283
Efstratiou AEfstratiou MYudhoatmojo SBlackburn JDe Cristofaro E(2024)"Here's Your Evidence": False Consensus in Public Twitter Discussions of COVID-19 ScienceProceedings of the ACM on Human-Computer Interaction10.1145/36870108:CSCW2(1-33)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687010
Godinez LMustafaraj E(2024)YouTube and Conspiracy Theories: A Longitudinal Audit of Information PanelsProceedings of the 35th ACM Conference on Hypertext and Social Media10.1145/3648188.3675128(273-284)Online publication date: 10-Sep-2024
https://dl.acm.org/doi/10.1145/3648188.3675128
Tang HLenzini GGreiff SRohles BSergeeva A(2024)“Who Knows? Maybe it Really Works”: Analysing Users' Perceptions of Health Misinformation on Social MediaProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661510(1499-1517)Online publication date: 1-Jul-2024
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Wolf SFriedrich PHurtienne J(2024)Still Not a Lot of Research? Re-Examining HCI Research on Religion and SpiritualityExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3651058(1-15)Online publication date: 11-May-2024
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Hanley HKumar DDurumeric Z(2024)Specious Sites: Tracking the Spread and Sway of Spurious News Stories at Scale2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00171(1609-1627)Online publication date: 19-May-2024
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Lai CToriumi FYoshida M(2024)A multilingual analysis of pro Russian misinformation on Twitter during the Russian invasion of UkraineScientific Reports10.1038/s41598-024-60653-y14:1Online publication date: 2-May-2024
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Guo CZheng NGuo C(2023)Seeing is Not Believing: A Nuanced View of Misinformation Warning Efficacy on Video-Sharing Social Media PlatformsProceedings of the ACM on Human-Computer Interaction10.1145/36100857:CSCW2(1-35)Online publication date: 4-Oct-2023
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Liu LChen JCheng ZTai WZhou FFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Towards Trustworthy Rumor Detection with Interpretable Graph Structural LearningProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615228(4089-4093)Online publication date: 21-Oct-2023
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Domínguez Hernández AOwen RNielsen DMcConville R(2023)Ethical, political and epistemic implications of machine learning (mis)information classification: insights from an interdisciplinary collaboration between social and data scientistsJournal of Responsible Innovation10.1080/23299460.2023.222251410:1Online publication date: 7-Jul-2023
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