The COVID-19 Social Media Infodemic

March 10, 2020 ยท Declared Dead ยท ๐Ÿ› Scientific Reports

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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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