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The COVID-19 social media infodemic

Academic Article
Publication Date:
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 R0 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.
Iris type:
01.01 - Articolo in rivista
List of contributors:
Cinelli, Matteo; Quattrociocchi, Walter; Galeazzi, Alessandro; Valensise, Carlo Michele; Brugnoli, Emanuele; Schmidt, Ana Lucia; Zola, Paola; Zollo, Fabiana; Scala, Antonio
Authors of the University:
GALEAZZI ALESSANDRO
Handle:
https://www.research.unipd.it/handle/11577/3510733
Full Text:
https://www.research.unipd.it//retrieve/handle/11577/3510733/898909/s41598-020-73510-5.pdf
Published in:
SCIENTIFIC REPORTS
Journal
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