Mapping Extremist Discourse Communities on Telegram: The Case of the Russian Imperial Movement and Its Affiliates

04 December 2023, Version 3
This content is an early or alternative research output and has not been peer-reviewed at the time of posting.


Measuring extremist behavior and discourse online presents a significant methodological challenge largely due to the volume of content. This paper assesses the extent to which discourse communities created by extremists identified through qualitative analysis in prior research are present in a novel Telegram dataset and can be identified through Latent Dirichlet Allocation topic modeling and network analysis. It then compares the results of Louvian and Girvan-Newman network community detection methods and the topics assigned to each community to see if the underlying structure of association between topics is robust to the use of different community detection methods. The results indicate that it may be possible to map discourse communities through topic modeling and network analysis. However, the comparison of the algorithms is inconclusive. This work contributes to our understanding of how computational social science methods can be used to measure and analyze extremist use of the Internet at scale.


social media
network analysis
topic modeling
discourse communities

Supplementary weblinks


Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.