The COVID-19 social media infodemic

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Cinelli, Matteo, Quattrociocchi, Walter, Galeazzi, Alessandro, Valensise, Carlo Michele, Brugnoli, Emanuele, Schmidt, Ana Lucia, Zola, Paola, Zollo, Fabiana, Scala, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538912/
https://www.ncbi.nlm.nih.gov/pubmed/33024152
http://dx.doi.org/10.1038/s41598-020-73510-5
_version_ 1783590957161119744
author Cinelli, Matteo
Quattrociocchi, Walter
Galeazzi, Alessandro
Valensise, Carlo Michele
Brugnoli, Emanuele
Schmidt, Ana Lucia
Zola, Paola
Zollo, Fabiana
Scala, Antonio
author_facet Cinelli, Matteo
Quattrociocchi, Walter
Galeazzi, Alessandro
Valensise, Carlo Michele
Brugnoli, Emanuele
Schmidt, Ana Lucia
Zola, Paola
Zollo, Fabiana
Scala, Antonio
author_sort Cinelli, Matteo
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7538912
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-75389122020-10-08 The COVID-19 social media infodemic Cinelli, Matteo Quattrociocchi, Walter Galeazzi, Alessandro Valensise, Carlo Michele Brugnoli, Emanuele Schmidt, Ana Lucia Zola, Paola Zollo, Fabiana Scala, Antonio Sci Rep Article 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. Nature Publishing Group UK 2020-10-06 /pmc/articles/PMC7538912/ /pubmed/33024152 http://dx.doi.org/10.1038/s41598-020-73510-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Cinelli, Matteo
Quattrociocchi, Walter
Galeazzi, Alessandro
Valensise, Carlo Michele
Brugnoli, Emanuele
Schmidt, Ana Lucia
Zola, Paola
Zollo, Fabiana
Scala, Antonio
The COVID-19 social media infodemic
title The COVID-19 social media infodemic
title_full The COVID-19 social media infodemic
title_fullStr The COVID-19 social media infodemic
title_full_unstemmed The COVID-19 social media infodemic
title_short The COVID-19 social media infodemic
title_sort covid-19 social media infodemic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538912/
https://www.ncbi.nlm.nih.gov/pubmed/33024152
http://dx.doi.org/10.1038/s41598-020-73510-5
work_keys_str_mv AT cinellimatteo thecovid19socialmediainfodemic
AT quattrociocchiwalter thecovid19socialmediainfodemic
AT galeazzialessandro thecovid19socialmediainfodemic
AT valensisecarlomichele thecovid19socialmediainfodemic
AT brugnoliemanuele thecovid19socialmediainfodemic
AT schmidtanalucia thecovid19socialmediainfodemic
AT zolapaola thecovid19socialmediainfodemic
AT zollofabiana thecovid19socialmediainfodemic
AT scalaantonio thecovid19socialmediainfodemic
AT cinellimatteo covid19socialmediainfodemic
AT quattrociocchiwalter covid19socialmediainfodemic
AT galeazzialessandro covid19socialmediainfodemic
AT valensisecarlomichele covid19socialmediainfodemic
AT brugnoliemanuele covid19socialmediainfodemic
AT schmidtanalucia covid19socialmediainfodemic
AT zolapaola covid19socialmediainfodemic
AT zollofabiana covid19socialmediainfodemic
AT scalaantonio covid19socialmediainfodemic

Ejemplares similares