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Anatomy of an online misinformation network
Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5922526/ https://www.ncbi.nlm.nih.gov/pubmed/29702657 http://dx.doi.org/10.1371/journal.pone.0196087 |
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author | Shao, Chengcheng Hui, Pik-Mai Wang, Lei Jiang, Xinwen Flammini, Alessandro Menczer, Filippo Ciampaglia, Giovanni Luca |
author_facet | Shao, Chengcheng Hui, Pik-Mai Wang, Lei Jiang, Xinwen Flammini, Alessandro Menczer, Filippo Ciampaglia, Giovanni Luca |
author_sort | Shao, Chengcheng |
collection | PubMed |
description | Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network. |
format | Online Article Text |
id | pubmed-5922526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-59225262018-05-11 Anatomy of an online misinformation network Shao, Chengcheng Hui, Pik-Mai Wang, Lei Jiang, Xinwen Flammini, Alessandro Menczer, Filippo Ciampaglia, Giovanni Luca PLoS One Research Article Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network. Public Library of Science 2018-04-27 /pmc/articles/PMC5922526/ /pubmed/29702657 http://dx.doi.org/10.1371/journal.pone.0196087 Text en © 2018 Shao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Shao, Chengcheng Hui, Pik-Mai Wang, Lei Jiang, Xinwen Flammini, Alessandro Menczer, Filippo Ciampaglia, Giovanni Luca Anatomy of an online misinformation network |
title | Anatomy of an online misinformation network |
title_full | Anatomy of an online misinformation network |
title_fullStr | Anatomy of an online misinformation network |
title_full_unstemmed | Anatomy of an online misinformation network |
title_short | Anatomy of an online misinformation network |
title_sort | anatomy of an online misinformation network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5922526/ https://www.ncbi.nlm.nih.gov/pubmed/29702657 http://dx.doi.org/10.1371/journal.pone.0196087 |
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