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Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter
The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711025/ https://www.ncbi.nlm.nih.gov/pubmed/29194446 http://dx.doi.org/10.1371/journal.pone.0181405 |
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author | Benigni, Matthew C. Joseph, Kenneth Carley, Kathleen M. |
author_facet | Benigni, Matthew C. Joseph, Kenneth Carley, Kathleen M. |
author_sort | Benigni, Matthew C. |
collection | PubMed |
description | The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success in motivating both recruitment and “lone wolf” attacks. The present work explores a large community of Twitter users whose activity supports ISIS propaganda diffusion in varying degrees. Within this ISIS supporting community, we observe a diverse range of actor types, including fighters, propagandists, recruiters, religious scholars, and unaffiliated sympathizers. The interaction between these users offers unique insight into the people and narratives critical to ISIS’ sustainment. In their entirety, we refer to this diverse set of users as an online extremist community or OEC. We present Iterative Vertex Clustering and Classification (IVCC), a scalable analytic approach for OEC detection in annotated heterogeneous networks, and provide an illustrative case study of an online community of over 22,000 Twitter users whose online behavior directly advocates support for ISIS or contibutes to the group’s propaganda dissemination through retweets. |
format | Online Article Text |
id | pubmed-5711025 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57110252017-12-15 Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter Benigni, Matthew C. Joseph, Kenneth Carley, Kathleen M. PLoS One Research Article The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success in motivating both recruitment and “lone wolf” attacks. The present work explores a large community of Twitter users whose activity supports ISIS propaganda diffusion in varying degrees. Within this ISIS supporting community, we observe a diverse range of actor types, including fighters, propagandists, recruiters, religious scholars, and unaffiliated sympathizers. The interaction between these users offers unique insight into the people and narratives critical to ISIS’ sustainment. In their entirety, we refer to this diverse set of users as an online extremist community or OEC. We present Iterative Vertex Clustering and Classification (IVCC), a scalable analytic approach for OEC detection in annotated heterogeneous networks, and provide an illustrative case study of an online community of over 22,000 Twitter users whose online behavior directly advocates support for ISIS or contibutes to the group’s propaganda dissemination through retweets. Public Library of Science 2017-12-01 /pmc/articles/PMC5711025/ /pubmed/29194446 http://dx.doi.org/10.1371/journal.pone.0181405 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Benigni, Matthew C. Joseph, Kenneth Carley, Kathleen M. Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter |
title | Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter |
title_full | Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter |
title_fullStr | Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter |
title_full_unstemmed | Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter |
title_short | Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter |
title_sort | online extremism and the communities that sustain it: detecting the isis supporting community on twitter |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711025/ https://www.ncbi.nlm.nih.gov/pubmed/29194446 http://dx.doi.org/10.1371/journal.pone.0181405 |
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