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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...

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Autores principales: Shao, Chengcheng, Hui, Pik-Mai, Wang, Lei, Jiang, Xinwen, Flammini, Alessandro, Menczer, Filippo, Ciampaglia, Giovanni Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
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.
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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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