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

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.

Graph Learning in 4D: A Quaternion-Valued Laplacian to Enhance Spectral GCNs

“…We experiment on the six widely-used real-world directed graphs Bitcoin-OTC, Bitcoin Alpha, WikiRfa, Telegram, Slashdot, and Epinions (see Kumar et al (2016); Bovet and Grindrod (2020); West et al (2014); Leskovec, Huttenlocher, and Kleinberg ( 2010)). The first three feature edge weights of unrestricted sign and magnitude; the fourth contains graphs with positive edge weights, while the last two have graphs with weights satisfying A ∈ {−1, 0, +1} n×n .…”