Research Article (Preprint): “The COVID-19 Social Media Infodemic”

The following article (preprint) was recently shared on arXiv. 

Title

The COVID-19 Social Media Infodemic

Authors

Matteo Cinelli
CNR-ISC

Walter Quattrociocchi
Universit Ca Foscari di Venezia
CNR-ISC
3Big Data in Health Society, Roma

Alessandro Galeazzi
Universit di Brescia

Carlo Michele Valensise
Politecnico di Milano

Emanuele Brugnoli
CNR-ISC

Ana Lucia Schmidt
Universit Ca Foscari di Venezia

Paola Zola
CNR-IIT

Fabiana Zollo
Universit Ca Foscari di Venezia
CNR-ISC

Antonio Scala
CNR-ISC
3Big Data in Health Society, Roma

Source

via arXiv
March 10, 2020

Abstract

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 numbers R0 for each social media platform. Moreover, we characterize 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.

Direct to Full Text Article (Preprint)

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