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10.1038/s41598-020-73510-5 http://scihub22266oqcxt.onion/10.1038/s41598-020-73510-5 33024152!7538912!33024152     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33024152&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Sci+Rep 2020 ; 10 (1): 16598 Nephropedia Template TP {{tp|p=33024152|t=2020. The COVID-19 social media infodemic |pdf=|usr=}}{{33024152}} gab.com Text The COVID-19 social media infodemic JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33024152 #FOAvip 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. 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. Twit Text FOAVip The COVID-19 social media infodemic ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33024152 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33024152 #FOAvip English Wikipedia <ref>{{Cite pmid|33024152}}</ref> The COVID-19 social media infodemic #MMPMID33024152 Cinelli M; Quattrociocchi W; Galeazzi A; Valensise CM; Brugnoli E; Schmidt AL; Zola P; Zollo F; Scala A Sci Rep 2020[Oct]; 10 (1): 16598 PMID33024152show ga 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. 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. |*Betacoronavirus[MESH] |*Social Media[MESH] |Basic Reproduction Number[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology/virology[MESH] |Data Analysis[MESH] |Humans[MESH] |Information Dissemination[MESH] |Linear Models[MESH] |Neural Networks, Computer[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology/virology[MESH] |SARS-CoV-2[MESH]The COVID-19 social media infodemic (epmc).pdf DeepDyve Pubget Overpricing