2025 NAACL NAACL 2025

Interpretable Models for Detecting Linguistic Variation in Russian Media: Towards Unveiling Propagandistic Strategies during the Russo-Ukrainian War

Abstract

AbstractWith the start of the full-scale Russian invasion of Ukraine in February 2022, the spread of pro-Kremlin propaganda increased to justify the war, both in the official state media and social media. This position paper explores the theoretical background of propaganda detection in the given context and proposes a thorough methodology to investigate how language has been strategically manipulated to align with ideological goals and adapt to the changing narrative surrounding the invasion. Using the WarMM-2022 corpus, the study seeks to identify linguistic patterns across media types and their evolution over time. By doing so, we aim to enhance the understanding of the role of linguistic strategies in shaping propaganda narratives. The findings are intended to contribute to the broader discussion of information manipulation in politically sensitive contexts.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Interdisciplinary and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio