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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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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. |
format | Online Article Text |
id | pubmed-10289895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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