Studying the COVID-19 infodemic at scale

被引：23

作者：

Gruzd, Anatoliy ^{[1
]}

De Domenico, Manlio ^{[2
]}

Sacco, Pier Luigi ^{[3
,4
]}

Briand, Sylvie ^{[5
]}

机构：

[1] Ryerson Univ, Ted Rogers Sch Management, Toronto, ON, Canada

[2] Fdn Bruno Kessler, CoMuNe Lab, Povo, Italy

[3] IULM Univ, Dept Humanities, Milan, Italy

[4] MetaLAB Harvard, Cambridge, MA USA

[5] World Hlth Org, Global Infect Hazards Preparedness Emergency Prep, Geneva, Switzerland

来源：

BIG DATA & SOCIETY | 2021年 / 8卷 / 01期

基金：

加拿大健康研究院;

关键词：

Infodemic; COVID-19; social media; misinformation; pandemic;

D O I：

10.1177/20539517211021115

中图分类号：

C [社会科学总论];

学科分类号：

03 ; 0303 ;

摘要：

This special theme issue of Big Data & Society presents leading-edge, interdisciplinary research that focuses on examining how health-related (mis-)information is circulating on social media. In particular, we are focusing on how computational and Big Data approaches can help to provide a better understanding of the ongoing COVID-19 infodemic (overexposure to both accurate and misleading information on a health topic) and to develop effective strategies to combat it.

引用

页数：6

共 32 条

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