Propaganda Detection in Russian Telegram Posts in the Scope of the Russian Invasion of Ukraine

Natalia Vanetik, Marina Litvak, Egor Reviakin, Margarita Tyamanova

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The emergence of social media has made it more difficult to recognize and analyze misinformation efforts. Popular messaging software Telegram (Durov, 2013) has developed into a medium for disseminating political messages and misinformation, particularly in light of the conflict in Ukraine (Wikipedia contributors, 2023). In this paper, we introduce a sizable corpus of Telegram posts containing pro-Russian propaganda and benign political texts. We evaluate the corpus by applying natural language processing (NLP) techniques to the task of text classification in this corpus. Our findings indicate that, with an overall accuracy of over 96% for confirmed sources as propagandists and oppositions and 92% for unconfirmed sources, our method can successfully identify and categorize pro-Russian propaganda posts. We highlight the consequences of our research for comprehending political communications and propaganda on social media.

Original languageEnglish
Title of host publicationInternational Conference Recent Advances in Natural Language Processing, RANLP 2023
Subtitle of host publicationLarge Language Models for Natural Language Processing - Proceedings
EditorsGalia Angelova, Maria Kunilovskaya, Ruslan Mitkov
PublisherIncoma Ltd
Pages1162-1170
Number of pages9
ISBN (Electronic)9789544520922
DOIs
StatePublished - 1 Jan 2023
Externally publishedYes
Event2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023 - Varna, Bulgaria
Duration: 4 Sep 20236 Sep 2023

Publication series

NameInternational Conference Recent Advances in Natural Language Processing, RANLP
ISSN (Print)1313-8502

Conference

Conference2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023
Country/TerritoryBulgaria
CityVarna
Period4/09/236/09/23

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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