Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

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

View through CrossRef
Abstract The instant messaging platform Telegram has become popular among the far-right movements in the US and UK in recent years. These group 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 the 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.
Research Square Platform LLC
Title: Organization and evolution of the UK far-right network on Telegram
Description:
Abstract The instant messaging platform Telegram has become popular among the far-right movements in the US and UK in recent years.
These group 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 the 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.

Related Results

The Role Telegram Application for Information Sharing in the Case of Online Ge’ez Language Learning
The Role Telegram Application for Information Sharing in the Case of Online Ge’ez Language Learning
Abstract Telegram is one of the application, which used for learning language in the online. The current study was aimed investigate how online learning resources facilitat...
PEMANFAATAN BOT TELEGRAM SEBAGAI E-LEARNING UJIAN BERBASIS FILE
PEMANFAATAN BOT TELEGRAM SEBAGAI E-LEARNING UJIAN BERBASIS FILE
E-learning merupakan sebuah sistem pendidikan yang menerapkan aplikasi elektronik yang mendukung peningkatan pendidikan dan latihan pembelajaran menggunakan media internet. Dengan ...
Effectiveness of telegram bot medical records with dentistry manual status card for forensic identification purposes
Effectiveness of telegram bot medical records with dentistry manual status card for forensic identification purposes
Background: Based on PERMENKES 2022 Number 24, it states that all health facilities are required to use electronic medical records in accordance with the regulation of the Minister...
The Effectiveness of Telegram as an Online Learning Media
The Effectiveness of Telegram as an Online Learning Media
Learning media is the main supporting factor that is needed to support the learning process, especially at this time which requires educators to design learning media as an innovat...
IMPLEMENTASI API BOT TELEGRAM UNTUK SISTEM NOTIFIKASI LIBRENMS PADA PERUSAHAAN BLIP INTEGRATOR
IMPLEMENTASI API BOT TELEGRAM UNTUK SISTEM NOTIFIKASI LIBRENMS PADA PERUSAHAAN BLIP INTEGRATOR
Teknologi Informasi lebih mudah dan cepat untuk didapat kapan saja dan dimana saja, Teknologi pada dasarnya memiliki tujuan untuk mempermudah manusia dalam melakukan sesuatu. Integ...
VEHICLE STARTER SYSTEM FOR SAFETY BASED MICROCONTROLLER USING INTERNET OF THINGS
VEHICLE STARTER SYSTEM FOR SAFETY BASED MICROCONTROLLER USING INTERNET OF THINGS
Technology is currently growing very fast which affects and has a significant purpose in human life. In the current era, the technology of the security system is something that is ...
The synergistic effect of ego-network stability and whole network position: a perspective of transnational coopetition network
The synergistic effect of ego-network stability and whole network position: a perspective of transnational coopetition network
PurposeThe authors selected global automobile manufacturing firms whose sales ranked within 100 in the five years from 2014 to 2018 in the Factiva database to examine how the chara...

Back to Top