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Organization and evolution of the UK far-right network on Telegram

The instant messaging platform Telegram has become popular among the far-right movements in the US and UK in recent years. These groups use public Telegram channels and group chats to disseminate hate speech, disinformation, and conspiracy theories. Recent works revealed that the far-right Telegram...

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Detalles Bibliográficos
Autores principales: Bovet, Alexandre, Grindrod, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667007/
https://www.ncbi.nlm.nih.gov/pubmed/36408456
http://dx.doi.org/10.1007/s41109-022-00513-8
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author Bovet, Alexandre
Grindrod, Peter
author_facet Bovet, Alexandre
Grindrod, Peter
author_sort Bovet, Alexandre
collection PubMed
description The instant messaging platform Telegram has become popular among the far-right movements in the US and UK in recent years. These groups use public Telegram channels and group chats to disseminate hate speech, disinformation, and conspiracy theories. Recent works revealed that the far-right Telegram network structure is decentralized and formed of several communities divided mostly along ideological and national lines. Here, we investigated the UK far-right network on Telegram and are interested in understanding the different roles of different channels and their influence relations. We apply a community detection method, based on the clustering of a flow of random walkers, that allows us to uncover the organization of the Telegram network in communities with different roles. We find three types of communities: (1) upstream communities contain mostly group chats that comment on content from channels in the rest of the network; (2) core communities contain broadcast channels tightly connected to each other and can be seen as forming echo chambers; (3) downstream communities contain popular channels that are highly referenced by other channels. We find that the network is composed of two main sub-networks: one containing mainly channels related to the English-speaking far-right movements and one with channels in Russian. We analyze the dynamics of the different communities and the most shared external links in the different types of communities over a period going from 2015 to 2020. We find that different types of communities have different dynamics and share links to different types of websites. We finish by discussing several directions for further work.
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spelling pubmed-96670072022-11-16 Organization and evolution of the UK far-right network on Telegram Bovet, Alexandre Grindrod, Peter Appl Netw Sci Research The instant messaging platform Telegram has become popular among the far-right movements in the US and UK in recent years. These groups use public Telegram channels and group chats to disseminate hate speech, disinformation, and conspiracy theories. Recent works revealed that the far-right Telegram network structure is decentralized and formed of several communities divided mostly along ideological and national lines. Here, we investigated the UK far-right network on Telegram and are interested in understanding the different roles of different channels and their influence relations. We apply a community detection method, based on the clustering of a flow of random walkers, that allows us to uncover the organization of the Telegram network in communities with different roles. We find three types of communities: (1) upstream communities contain mostly group chats that comment on content from channels in the rest of the network; (2) core communities contain broadcast channels tightly connected to each other and can be seen as forming echo chambers; (3) downstream communities contain popular channels that are highly referenced by other channels. We find that the network is composed of two main sub-networks: one containing mainly channels related to the English-speaking far-right movements and one with channels in Russian. We analyze the dynamics of the different communities and the most shared external links in the different types of communities over a period going from 2015 to 2020. We find that different types of communities have different dynamics and share links to different types of websites. We finish by discussing several directions for further work. Springer International Publishing 2022-11-15 2022 /pmc/articles/PMC9667007/ /pubmed/36408456 http://dx.doi.org/10.1007/s41109-022-00513-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Bovet, Alexandre
Grindrod, Peter
Organization and evolution of the UK far-right network on Telegram
title Organization and evolution of the UK far-right network on Telegram
title_full Organization and evolution of the UK far-right network on Telegram
title_fullStr Organization and evolution of the UK far-right network on Telegram
title_full_unstemmed Organization and evolution of the UK far-right network on Telegram
title_short Organization and evolution of the UK far-right network on Telegram
title_sort organization and evolution of the uk far-right network on telegram
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667007/
https://www.ncbi.nlm.nih.gov/pubmed/36408456
http://dx.doi.org/10.1007/s41109-022-00513-8
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