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arXiv:2003.05004cs.SI

The COVID-19 Social Media Infodemic

Matteo Cinelli, Walter Quattrociocchi, Alessandro Galeazzi, Carlo Michele Valensise, Emanuele Brugnoli, Ana Lucia Schmidt, Paola Zola, Fabiana Zollo, Antonio Scala

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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 $R_0$ 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.

arXiv comments
Journal reference
Sci Rep 10, 16598 (2020)
DOI
doi:10.1038/s41598-020-73510-5
Subjects
cs.SISocial and Information Networks nlin.AOAdaptation and Self-Organizing Systems physics.soc-phPhysics and Society

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