Propaganda and Information Dissemination in the Russo-Ukrainian War: Natural Language Processing of Russian and Western Twitter Narratives

Fuente: arXiv
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Auteur principal: Gouliev, Zaur
Format: Preprint
Publié: 2025
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author Gouliev, Zaur
author_facet Gouliev, Zaur
contents The conflict in Ukraine has been not only characterised by military engagement but also by a significant information war, with social media platforms like X, formerly known as Twitter playing an important role in shaping public perception. This article provides an analysis of tweets from propaganda accounts and trusted accounts collected from the onset of the war, February 2022 until the middle of May 2022 with n=40,000 total tweets. We utilise natural language processing and machine learning algorithms to assess the sentiment and identify key themes, topics and narratives across the dataset with human-in-the-loop (HITL) analysis throughout. Our findings indicate distinct strategies in how information is created, spread, and targeted at different audiences by both sides. Propaganda accounts frequently employ emotionally charged language and disinformation to evoke fear and distrust, whereas other accounts, primarily Western tend to focus on factual reporting and humanitarian aspects of the conflict. Clustering analysis reveals groups of accounts with similar behaviours, which we suspect indicates the presence of coordinated efforts. This research attempts to contribute to our understanding of the dynamics of information warfare and offers techniques for future studies on social media influence in military conflicts.
format Preprint
id arxiv_https___arxiv_org_abs_2506_01807
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Propaganda and Information Dissemination in the Russo-Ukrainian War: Natural Language Processing of Russian and Western Twitter Narratives
Gouliev, Zaur
Computation and Language
The conflict in Ukraine has been not only characterised by military engagement but also by a significant information war, with social media platforms like X, formerly known as Twitter playing an important role in shaping public perception. This article provides an analysis of tweets from propaganda accounts and trusted accounts collected from the onset of the war, February 2022 until the middle of May 2022 with n=40,000 total tweets. We utilise natural language processing and machine learning algorithms to assess the sentiment and identify key themes, topics and narratives across the dataset with human-in-the-loop (HITL) analysis throughout. Our findings indicate distinct strategies in how information is created, spread, and targeted at different audiences by both sides. Propaganda accounts frequently employ emotionally charged language and disinformation to evoke fear and distrust, whereas other accounts, primarily Western tend to focus on factual reporting and humanitarian aspects of the conflict. Clustering analysis reveals groups of accounts with similar behaviours, which we suspect indicates the presence of coordinated efforts. This research attempts to contribute to our understanding of the dynamics of information warfare and offers techniques for future studies on social media influence in military conflicts.
title Propaganda and Information Dissemination in the Russo-Ukrainian War: Natural Language Processing of Russian and Western Twitter Narratives
topic Computation and Language
url https://arxiv.org/abs/2506.01807