id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-254653-4ffuivil	Cinelli, Matteo	The COVID-19 social media infodemic	2020-10-06		.txt	text/plain	5100	289	50	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 [Formula: see text] for each social media platform. Unlike previous works, we do not only focus on models that imply specific growth mechanisms, but also on phenomenological models that emphasize the reproducibility of empirical data 41 www.nature.com/scientificreports/ Most of the epidemiological models focus on the basic reproduction number R 0 , representing the expected number of new infectors directly generated by an infected individual for a given time period 42 . Furthermore, we model the spread of information using epidemic models and provide basic growth parameters for each social media platform.	./cache/cord-254653-4ffuivil.txt	./txt/cord-254653-4ffuivil.txt