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Misinformation During the COVID-19 Outbreak in China: Cultural, Social and Political Entanglements
Ieee Transactions on Big Data ; 7(1):69-80, 2021.
Article in English | Web of Science | ID: covidwho-1195761
ABSTRACT
Not only did COVID-19 give rise to a global pandemic, but also it resulted in an infodemic comprising misinformation, rumor, and propaganda. The consequences of this infodemic can erode public trust, impede the containment of the virus, and outlive the pandemic itself. The evolving and fragmented media landscape, particularly the extensive use of social media, is a crucial driver of the spread of misinformation. Focusing on the Chinese social media Weibo, we collected four million tweets, from December 9, 2019, to April 4, 2020, examining misinformation identified by the fact-checking platform Tencent-a leading Chinese tech giant. Our results show that the evolution of misinformation follows an issue-attention cycle pertaining to topics such as city lockdown, cures and preventive measures, school reopening, and foreign countries. Sensational and emotionally reassuring misinformation characterizes the whole issue-attention cycle, with misinformation on cures and prevention flooding social media. We also study the evolution of sentiment and observe that positive sentiment dominated over the course of Covid, which may be due to the unique characteristic of "positive energy" on Chinese social media. Lastly, we study the media landscape during Covid via a case study on a controversial unproven cure known as Shuanghuanglian, which testifies to the importance of scientific communication in a plague. Our findings shed light on the distinct characteristics of misinformation and its cultural, social, and political implications, during the COVID-19 pandemic. The study also offers insights into combating misinformation in China and across the world at large.

Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Ieee Transactions on Big Data Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Ieee Transactions on Big Data Year: 2021 Document Type: Article