Linked in the dark: A network approach to understanding information flows within the Dutch Telegramsphere

Monika Simon, Kasper Welbers, Anne C. Kroon, Damian Trilling

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Recent studies have shown that the stricter content moderation policies imposed by mainstream social networking sites (SNSs) stimulated the growth of low-moderated but relatively open discussion platforms such as Telegram. Despite Telegram’s growing popularity among (deplatformed) digital exiles, and high potential for news dissemination, information consumption, mobilization, and radicalization, little is known about information flows with respect to politically and socially relevant topics within the Telegramsphere. We scrutinize the Telegramsphere as an information-sharing ecosystem of current affairs by uncovering how information flows indicated by content-overlap and shared users influenced the structure of Telegram networks and shaped communities over time. Using state-of-the-art web-mining, neural topic modeling, and social network analysis techniques on a unique data set that spans the full messaging history (N = 2,033,661) of 174 Dutch-language public Telegram chats/channels, we show that over time, conspiracy-themed, far-right activist, and COVID-19-sceptical communities dominated the Dutch Telegramsphere of current affairs. Our findings raise concerns with respect to Telegram’s polarization and radicalization capacity in the context of consuming socially and politically relevant information online.
Original languageEnglish
Pages (from-to)3054-3078
Number of pages25
JournalInformation, Communication and Society
Volume26
Issue number15
Early online date16 Oct 2022
DOIs
Publication statusPublished - 2023

Funding

This work is part of a project that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 947695). This work made use of the Dutch national e-infrastructure with the support of the SURF Cooperative using grant no. EINF-2968.

FundersFunder number
SURFEINF-2968
Horizon 2020 Framework Programme
European Research Council
Horizon 2020947695

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