Digital (Mis)Information: Lessons from Twitter and Sina Weibo in the Pandemic

• In Event: Digital Information Flows and Politics in the COVID-19 Pandemic

Abstract

Misinformation about COVID-19 has presented challenges to public health authorities during pandemics. This paper leverages qualitative and quantitative content analysis on cross-platform, cross-national discourse and misinformation in the context of COVID-19. Specifically, we investigate COVID-19-related content on Twitter and Sina Weibo – the largest microblogging sites in the United States and China respectively. We examine how the use and engagement measured by keyword frequencies and hashtags differ across the two platforms. We analyzed Twitter and Sina Weibo data that were posted within 24 hours of the World Health Organization (WHO) announcement of the pandemic as well as data one week later. With a dataset consisting of millions of posts, we take a 1% random sample of Tweets and Sina Weibo posts that contain keywords relating to COVID-19, employ the Viterbi algorithm, and manually code a random selection of 5-7% of the content. We find that many topics on Twitter and Sina Weibo overlapped, although Sina Weibo was less likely to reference death, the WHO, and Hong Kong, and more likely to issue messages intended to boost community morale.
Using data from two prominent microblogging platform, Twitter, based in the United States, and Sina Weibo, based in China, we compare the content and relative prevalence of misinformation to better understand public discourse of public health issues across social media and cultural contexts.
A total of 3,579,575 posts were scraped from both Sina Weibo and Twitter, focusing on content from January 30th, 2020, when the World Health Organization (WHO) declared COVID-19 a “Public Health Emergency of International Concern” and a week later, on February 6th, 2020. A 1% random sample of tweets that contained both the English keywords “coronavirus” and “covid-19” and the equivalent Chinese characters was extracted and analyzed based on changes in the frequencies of keywords and hashtags. Misinformation on each platform was compared by manually coding and comparing posts using the World Health Organization fact-check page to adjudicate accuracy of content.
Both platforms posted about the outbreak and transmission but posts on Sina Weibo were less likely to reference topics such as the World Health Organization and death and more likely to cite themes of resisting, fighting, and cheering against the coronavirus. Misinformation constituted 1.1% of Twitter content and 0.3% of Sina Weibo content – almost four times as much on Twitter compared to Sina Weibo.
Quantitative and qualitative analysis of content on both platforms points to lower degrees of misinformation, more content designed to bolster morale, and less reference to topics such as the World Health Organization, death, and Hong Kong, than on Twitter.

Authors

• Julie George, Cornell University

• Sarah E. Kreps