mlsanityData to 7 Oct 2026

Partial Mobilization: Tracking Multilingual Information Flows Amongst Russian Media Outlets and Telegram

arXiv 2301.10856 ↗First posted 25 Jan 2023cs.CY cs.CL cs.LGcited by 5

Not on the map. Why?

Abstract (arXiv)

In response to disinformation and propaganda from Russian online media following the invasion of Ukraine, Russian media outlets such as Russia Today and Sputnik News were banned throughout Europe. To maintain viewership, many of these Russian outlets began to heavily promote their content on messaging services like Telegram. In this work, we study how 16 Russian media outlets interacted with and utilized 732 Telegram channels throughout 2022. Leveraging the foundational model MPNet, DP-means clustering, and Hawkes processes, we trace how narratives spread between news sites and Telegram channels. We show that news outlets not only propagate existing narratives through Telegram but that they source material from the messaging platform. For example, across the websites in our study, between 2.3% (ura.news) and 26.7% (ukraina.ru) of articles discussed content that originated/resulted from activity on Telegram. Finally, tracking the spread of individual topics, we measure the rate at which news outlets and Telegram channels disseminate content within the Russian media ecosystem, finding that websites like ura.news and Telegram channels such as @genshab are the most effective at disseminating their content.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 14 of its 73 references that are in the map. First posted on arXiv 25 Jan 2023.

Builds on

14 of 73 references.

References · 14

  1. 2020MPNet: Masked and Permuted Pre-training for Language Understandingcited by 973
  2. 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 789
  3. 2018On the Origins of Memes by Means of Fringe Web Communitiescited by 45
  4. 2018Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaigncited by 30
  5. 2021On the Globalization of the QAnon Conspiracy Theory Through Telegramcited by 14
  6. 2020The Pushshift Telegram Datasetcited by 12
  7. 2022Happenstance: Utilizing Semantic Search to Track Russian State Media Narratives about the Russo-Ukrainian War On Redditcited by 11
  8. 2022Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Mediacited by 10
  9. 2015Scalable Bayesian Inference for Excitatory Point Process Networkscited by 9
  10. 2022Overcoming Language Disparity in Online Content Classification with Multimodal Learningcited by 8
  11. 2021No Calm in The Storm: Investigating QAnon Website Relationshipscited by 5
  12. 2021Uncovering the Dark Side of Telegram: Fakes, Clones, Scams, and Conspiracy Movementscited by 5
2 more
  1. 2022"A Special Operation": A Quantitative Approach to Dissecting and Comparing Different Media Ecosystems' Coverage of the Russo-Ukrainian Warcited by 4
  2. 2022Using Sentence Embeddings and Semantic Similarity for Seeking Consensus when Assessing Trustworthy AIcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 1; 2026: 1.

5 papers.