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了解新冠疫情推特信息流上高质量和低质量的网址分享情况。

Understanding high- and low-quality URL Sharing on COVID-19 Twitter streams.

作者信息

Singh Lisa, Bode Leticia, Budak Ceren, Kawintiranon Kornraphop, Padden Colton, Vraga Emily

机构信息

Georgetown University, Washington, DC, USA.

University of Michigan, Ann Arbor, USA.

出版信息

J Comput Soc Sci. 2020;3(2):343-366. doi: 10.1007/s42001-020-00093-6. Epub 2020 Nov 27.

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.

摘要

本文调查了用户在推特上讨论新冠疫情时分享的高质量和低质量网址的流行情况。我们区分了高质量健康信息源、传统新闻源和低质量错误信息源。我们发现,就包含来自低质量错误信息网站网址的推文而言,错误信息的分享率高于包含高质量健康信息网站网址的推文。然而,这两者在整体讨论中所占比例都相对较小。相比之下,新闻源的分享率要高得多。这些发现促使我们分析推特用户分享的网页中所引用网址构成的网络。当观察由所有三种源类型构成的综合网络时,我们发现高质量健康信息网络、低质量错误信息网络和新闻信息网络都联系紧密,具有清晰的社区结构。虽然高质量和低质量网站之间确实存在联系,但与新闻源的往来联系更为常见,这凸显了新闻源在这个信息生态系统中所起的核心中介作用。我们的研究结果表明,虽然在新冠疫情推特讨论中低质量网址没有被广泛分享,但网络上已经出现了一个联系紧密的与新冠疫情相关的低质量信息社区,健康信息源和新闻源都与这个社区有联系。

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