The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
What they do in the shadows: examining the far-right networks on Telegram
Abstract
The present paper contributes to the research on the activities of far-right actors on social media by examining the interconnections between far-right actors and groups on Telegram platform using network analysis. The far-right network observed on Telegram is highly decentralized, similarly to the far-right networks found on other social media platforms. The network is divided mostly along the ideological and national lines, with the communities related to 4chan imageboard and Donald Trump’s supporters being the most influential. The analysis of the network evolution shows that the start of its explosive growth coincides in time with the mass bans of the far-right actors on mainstream social media platforms. The observed patterns of network evolution suggest that the simultaneous migration of these actors to Telegram has allowed them to swiftly recreate their connections and gain prominence in the network thus casting doubt on the effectiveness of deplatforming for curbing the influence of far-right and other extremist actors.
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null (2016) · Philosophy Study · doi:10.17265/2159-5313/2016.09.003 · Cited by 28,317
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Snowball Sampling: Problems and Techniques of Chain Referral Sampling
Biernacki, P., & Waldorf, D. (1981) · Sociological Methods & Research · doi:10.1177/004912418101000205 · Cited by 5,464
Populist Radical Right Parties in Europe
Mudde, C. (2007) · doi:10.1017/cbo9780511492037 · Cited by 4,694
Goodman, L. A. (1961) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177705148 · Cited by 3,606
Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098679 · Cited by 2,909
Authoritative sources in a hyperlinked environment
Kleinberg, J. M. (1998) · Symposium on Discrete Algorithms · doi:10.5555/314613.315045 · Cited by 1,814
Populist radical Right parties in Europe
(2008) · Choice Reviews Online · doi:10.5860/choice.45-5219 · Cited by 1,594
Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks
Gould, R. V., & Fernandez, R. M. (1989) · Sociological Methodology · doi:10.2307/270949 · Cited by 1,332
Cited by
Evaluating the Effectiveness of Deplatforming as a Moderation Strategy on Twitter
Jhaver, S., Boylston, C., Yang, D., & Bruckman, A. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479525 · Cited by 169
Are Anti-Feminist Communities Gateways to the Far Right? Evidence from Reddit and YouTube
Mamié, R., Horta Ribeiro, M., & West, R. (2021) · 13th ACM Web Science Conference 2021 · doi:10.1145/3447535.3462504 · Cited by 75
Cross-Platform Reactions to the Post-January 6 Deplatforming
Buntain, C., Innes, M., Mitts, T., & Shapiro, J. (2023) · Journal of Quantitative Description: Digital Media · doi:10.51685/jqd.2023.004 · Cited by 25
Metadata
- Authors
- Urman, A., & Katz, S.
- Venue
- Information, Communication & Society
- Publisher
- Informa UK Limited
- Published
- 2020-08-20
- Volume
- 25
- Issue
- 7
- Pages
- 904-923
- ISSN
- 1369-118X (ISSN-L)
- 1468-4462
- OpenAlex
- W3078122429
- Cited by
- 259
- References
- 36
- FWCI
- 105.40
- Type
- journal article
- Language
- en
- Open access
- closed
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