Understanding high- and low-quality URL Sharing on COVID-19 Twitter streams
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Understanding high‑ and low‑quality URL Sharing on COVID‑19 Twitter streams Lisa Singh1 · Leticia Bode1 · Ceren Budak2 · Kornraphop Kawintiranon1 · Colton Padden1 · Emily Vraga3 Received: 16 July 2020 / Accepted: 23 October 2020 / Published online: 27 November 2020 © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature 2020
Abstract This article investigates the prevalence of high and low quality URLs shared on Twitter when users discuss COVID-19. We distinguish between high quality health sources, traditional news sources, and low quality misinformation sources. We find that misinformation, in terms of tweets containing URLs from low quality misinformation websites, is shared at a higher rate than tweets containing URLs on high quality health information websites. However, both are a relatively small proportion of the overall conversation. In contrast, news sources are shared at a much higher rate. These findings lead us to analyze the network created by the URLs referenced on the webpages shared by Twitter users. When looking at the combined network formed by all three of the source types, we find that the high quality health information network, the low quality misinformation network, and the news information network are all well connected with a clear community structure. While high and low quality sites do have connections to each other, the connections to and from news sources are more common, highlighting the central brokerage role news sources play in this information ecosystem. Our findings suggest that while low quality URLs are not extensively shared in the COVID-19 Twitter conversation, a well connected community of low quality COVID-19 related information has emerged on the web, and both health and news sources are connecting to this community. Keywords COVID-19 · Coronavirus · Twitter conversation · Misinformation · Low quality domains
* Lisa Singh [email protected] 1
Georgetown University, Washington, DC, USA
2
University of Michigan, Ann Arbor, USA
3
University of Minnesota, Minneapolis, USA
13
Vol.:(0123456789)
344
Journal of Computational Social Science (2020) 3:343–366
Introduction Social media are a significant conduit for news and information in the modern media environment, with one in three people in the world engaging in social media, and two thirds of those on the Internet using it [44]. The popularity is higher in the United States with 68% of American adults reporting that they get their news on social media [37]. This is particularly true for health and science information, with a third of people reporting that social media are an “important” source of science news [29]. Twitter, in particular, is known for sharing and consuming news: 59% of its users describing it as “good” or “extremely good” for sharing preventive health information [63]. Of course, there is a great deal of research that examines the existence and spread of misinformation on Twitter [3, 14, 53], including that spread by bots [21, 50]. Most not
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