2026 EACL EACL 2026

Modeling Linguistic Imprints of War Propaganda in a Russian Wikipedia Fork: A Comparative Analysis with the Original Wikipedia

Abstract

AbstractAlthough Wikipedia aspires to provide neutral information, alternative versions can be used for political manipulation. This paper analyzes how narratives about the Russo-Ukrainian War are linguistically reframed in a Russian Wikipedia Fork compared to the original Russian Wikipedia. Using Kullback-Leibler Divergence on a corpus of war-related edits in more than 13,000 articles, we identify key differences between the two versions. While the original Wikipedia features Ukrainian references and administrative details, direct war terminology, and Ukraine’s territorial designation, governance, and statehood, RWFork replaces or removes these elements, emphasizing reassignment of Ukrainian territories to Russia, favoring euphemistic war language, renaming locations, and recognizing Russia-backed DPR and LPR. These patterns closely align RWFork with demobilizational strategies observed in pro-Kremlin media.

🧭 Keyword Pioneer — linguistic framing
🐝 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, Speech & Audio