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 R 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.
The COVID-19 social media infodemic / Cinelli, M.; Quattrociocchi, W.; Galeazzi, A.; Valensise, C. M.; Brugnoli, E.; Schmidt, A. L.; Zola, P.; Zollo, F.; Scala, A.. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 10:1(2020), p. 16598. [10.1038/s41598-020-73510-5]
The COVID-19 social media infodemic
Cinelli M.;Quattrociocchi W.
;Galeazzi A.;Valensise C. M.;Brugnoli E.;
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 number R 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
