Organization and evolution of the UK far-right network on Telegram
Bibliographic Data
| ID | 7534780 |
|---|---|
| Authors | Alain Bovet (0000-0003-3937-3704, University of Zurich, corresponding author), Alexandre Bovet, Peter Grindrod (0000-0002-0934-5131, University of Oxford) |
| Year | 2022 |
| Volume | 7 |
| Issue | 1 |
| Pages | 76-76 |
| Publication date | 2022-11-15 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Applied Network Science (JOURNAL) |
| Journal identifiers | ISSN: 2364-8228 • E-ISSN: 2364-8228 |
| Publisher | Springer Nature (PUBLISHER • SG) |
| DOI | 10.1007/s41109-022-00513-8 |
| PMID | 36408456 |
| OpenAlex | W4309347841 |
| Language | EN |
| Citations received | 9 |
| References cited | 22 |
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
Computer security · Disinformation · Ideology · Political science · Politics · Social media · Telecommunications · World Wide Web · Computer Science · Law · Opinion Dynamics and Social Influence · Populism, Right-Wing Movements · Social Media and Politics
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The online exchange of conspiracy theories within an Irish extreme right wing Telegram group during the Covid-19 pandemic
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| Citations per year | 3 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |