The COVID-19 social media infodemic

被引：1058

作者：

Cinelli, Matteo ^{[1
,2
]}

Quattrociocchi, Walter ^{[1
,2
,3
]}

Galeazzi, Alessandro ^{[4
]}

Valensise, Carlo Michele ^{[5
]}

Brugnoli, Emanuele ^{[1
]}

Schmidt, Ana Lucia ^{[2
]}

Zola, Paola ^{[6
]}

Zollo, Fabiana ^{[1
,2
,7
]}

Scala, Antonio ^{[1
,3
]}

机构：

[1] CNR, ISC, Rome, Italy

[2] Univ Ca Foscari Venezia, Venice, Italy

[3] Big Data Hlth Soc, Rome, Italy

[4] Univ Brescia, Brescia, Italy

[5] Politecn Milan, Milan, Italy

[6] CNR, IIT, Pisa, Italy

[7] Ctr Humanities & Social Change, Venice, Italy

来源：

SCIENTIFIC REPORTS | 2020年 / 10卷 / 01期

关键词：

NEWS; TWITTER; SPREAD;

D O I：

10.1038/s41598-020-73510-5

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading with epidemic models characterizing the basic reproduction number R0 for each social media platform. Moreover, we identify information spreading from questionable sources, finding different volumes of misinformation in each platform. However, information from both reliable and questionable sources do not present different spreading patterns. Finally, we provide platform-dependent numerical estimates of rumors' amplification.

引用

页数：10

共 51 条

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