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The Discussions of Monkeypox Misinformation on Social Media

Author

Listed:
  • Or Elroy

    (Department of Computer Science, University of Oregon, Eugene, OR 97403, USA)

  • Abraham Yosipof

    (Faculty of Information Systems and Computer Science, College of Law & Business, Ramat-Gan, P.O. Box 852, Bnei Brak 5110801, Israel
    International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

Abstract

The global outbreak of the monkeypox virus was declared a health emergency by the World Health Organization (WHO). During such emergencies, misinformation about health suggestions can spread rapidly, leading to serious consequences. This study investigates the relationships between tweet readability, user engagement, and susceptibility to misinformation. Our conceptual model posits that tweet readability influences user engagement, which in turn affects the spread of misinformation. Specifically, we hypothesize that tweets with higher readability and grammatical correctness garner more user engagement and that misinformation tweets tend to be less readable than accurate information tweets. To test these hypotheses, we collected over 1.4 million tweets related to monkeypox discussions on X (formerly Twitter) and trained a semi-supervised learning classifier to categorize them as misinformation or not-misinformation. We analyzed the readability and grammar levels of these tweets using established metrics. Our findings indicate that readability and grammatical correctness significantly boost user engagement with accurate information, thereby enhancing its dissemination. Conversely, misinformation tweets are generally less readable, which reduces their spread. This study contributes to the advancement of knowledge by elucidating the role of readability in combating misinformation. Practically, it suggests that improving the readability and grammatical correctness of accurate information can enhance user engagement and consequently mitigate the spread of misinformation during health emergencies. These insights offer valuable strategies for public health communication and social media platforms to more effectively address misinformation.

Suggested Citation

  • Or Elroy & Abraham Yosipof, 2025. "The Discussions of Monkeypox Misinformation on Social Media," Data, MDPI, vol. 10(9), pages 1-18, August.
  • Handle: RePEc:gam:jdataj:v:10:y:2025:i:9:p:137-:d:1731704
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    References listed on IDEAS

    as
    1. Zhichao Fang & Rodrigo Costas & Paul Wouters, 2022. "User engagement with scholarly tweets of scientific papers: a large-scale and cross-disciplinary analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4523-4546, August.
    2. Myeong Gyu Kim & Minjung Kim & Jae Hyun Kim & Kyungim Kim, 2022. "Fine-Tuning BERT Models to Classify Misinformation on Garlic and COVID-19 on Twitter," IJERPH, MDPI, vol. 19(9), pages 1-9, April.
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