The COVID-19 Social Media Infodemic
March 10, 2020 ยท Declared Dead ยท ๐ Scientific Reports
"No code URL or promise found in abstract"
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Authors
Matteo Cinelli, Walter Quattrociocchi, Alessandro Galeazzi, Carlo Michele Valensise, Emanuele Brugnoli, Ana Lucia Schmidt, Paola Zola, Fabiana Zollo, Antonio Scala
arXiv ID
2003.05004
Category
cs.SI: Social & Info Networks
Cross-listed
nlin.AO,
physics.soc-ph
Citations
1.8K
Venue
Scientific Reports
Last Checked
1 month ago
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.
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