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Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections

Social media has been transforming political communication dynamics for over a decade. Here using nearly a billion tweets, we analyse the change in Twitter’s news media landscape between the 2016 and 2020 US presidential elections. Using political bias and fact-checking tools, we measure the volume...

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Autores principales: Flamino, James, Galeazzi, Alessandro, Feldman, Stuart, Macy, Michael W., Cross, Brendan, Zhou, Zhenkun, Serafino, Matteo, Bovet, Alexandre, Makse, Hernán A., Szymanski, Boleslaw K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289895/
https://www.ncbi.nlm.nih.gov/pubmed/36914806
http://dx.doi.org/10.1038/s41562-023-01550-8
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author Flamino, James
Galeazzi, Alessandro
Feldman, Stuart
Macy, Michael W.
Cross, Brendan
Zhou, Zhenkun
Serafino, Matteo
Bovet, Alexandre
Makse, Hernán A.
Szymanski, Boleslaw K.
author_facet Flamino, James
Galeazzi, Alessandro
Feldman, Stuart
Macy, Michael W.
Cross, Brendan
Zhou, Zhenkun
Serafino, Matteo
Bovet, Alexandre
Makse, Hernán A.
Szymanski, Boleslaw K.
author_sort Flamino, James
collection PubMed
description Social media has been transforming political communication dynamics for over a decade. Here using nearly a billion tweets, we analyse the change in Twitter’s news media landscape between the 2016 and 2020 US presidential elections. Using political bias and fact-checking tools, we measure the volume of politically biased content and the number of users propagating such information. We then identify influencers—users with the greatest ability to spread news in the Twitter network. We observe that the fraction of fake and extremely biased content declined between 2016 and 2020. However, results show increasing echo chamber behaviours and latent ideological polarization across the two elections at the user and influencer levels.
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spelling pubmed-102898952023-06-25 Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections Flamino, James Galeazzi, Alessandro Feldman, Stuart Macy, Michael W. Cross, Brendan Zhou, Zhenkun Serafino, Matteo Bovet, Alexandre Makse, Hernán A. Szymanski, Boleslaw K. Nat Hum Behav Article Social media has been transforming political communication dynamics for over a decade. Here using nearly a billion tweets, we analyse the change in Twitter’s news media landscape between the 2016 and 2020 US presidential elections. Using political bias and fact-checking tools, we measure the volume of politically biased content and the number of users propagating such information. We then identify influencers—users with the greatest ability to spread news in the Twitter network. We observe that the fraction of fake and extremely biased content declined between 2016 and 2020. However, results show increasing echo chamber behaviours and latent ideological polarization across the two elections at the user and influencer levels. Nature Publishing Group UK 2023-03-13 2023 /pmc/articles/PMC10289895/ /pubmed/36914806 http://dx.doi.org/10.1038/s41562-023-01550-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Flamino, James
Galeazzi, Alessandro
Feldman, Stuart
Macy, Michael W.
Cross, Brendan
Zhou, Zhenkun
Serafino, Matteo
Bovet, Alexandre
Makse, Hernán A.
Szymanski, Boleslaw K.
Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections
title Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections
title_full Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections
title_fullStr Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections
title_full_unstemmed Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections
title_short Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections
title_sort political polarization of news media and influencers on twitter in the 2016 and 2020 us presidential elections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289895/
https://www.ncbi.nlm.nih.gov/pubmed/36914806
http://dx.doi.org/10.1038/s41562-023-01550-8
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