A Longitudinal, Multinational, and Multilingual Corpus of News Coverage of the Russo-Ukrainian War

TL;DR

DNIPRO is a large, multilingual news corpus from the Russo-Ukrainian war, enabling systematic analysis of media narratives, framing, and information warfare across countries and languages.

Contribution

It introduces a comprehensive, annotated news corpus covering multiple countries and languages, facilitating empirical studies of media narratives and information flow.

Findings

Media outlets construct incompatible realities through divergent framing.

The corpus enables analysis of narrative divergence and cross-lingual information flow.

It supports computational detection of implicit contradictions in media narratives.

Abstract

We present DNIPRO, a corpus of 246K news articles from the Russo-Ukrainian war (Feb 2022 -- Aug 2024) spanning eleven outlets across five nation-states (Russia, Ukraine, U.S., U.K., China) and three languages. The corpus features comprehensive metadata and human-evaluated annotations for stance, sentiment, and topical framing, enabling systematic analysis of competing geopolitical narratives. It is uniquely suited for empirical studies of narrative divergence, media framing, and information warfare. Our exploratory analyses reveal how media outlets construct incompatible realities through divergent attribution and topical selection without direct refutation of opposing narratives. DNIPRO empowers empirical research on narrative evolution, cross-lingual information flow, and computational detection of implicit contradictions in fragmented information ecosystems.