This work introduces EUvsDisinfo, a multilingual dataset of trustworthy and
disinformation articles related to pro-Kremlin themes. It is sourced directly
from the debunk articles written by experts leading the EUvsDisinfo project.
Our dataset is the largest to-date resource in terms of the overall number of
articles and distinct languages. It also provides the largest topical and
temporal coverage. Using this dataset, we investigate the dissemination of
pro-Kremlin disinformation across different languages, uncovering
language-specific patterns targeting specific disinformation topics. We further
analyse the evolution of topic distribution over an eight-year period, noting a
significant surge in disinformation content before the full-scale invasion of
Ukraine in 2022. Lastly, we demonstrate the dataset's applicability in training
models to effectively distinguish between disinformation and trustworthy
content in multilingual settings.

本研究介绍了 EUvsDisinfo，这是一个可信与虚假信息文章的多语种数据集，与亲克里姆林宫主题相关。该数据集直接来源于 EUvsDisinfo 项目专家撰写的辟谣文章。我们的数据集是迄今为止在文章数量和不同语言方面规模最大的资源。它还提供了最广泛的主题和时间覆盖范围。利用这个数据集，我们调查了亲克里姆林宫虚假信息在不同语言中的传播情况，揭示了针对特定虚假信息主题的语言特定模式。我们进一步分析了八年期间话题分布的演变，并注意到在 2022 年乌克兰全面入侵之前，虚假信息内容急剧增加。最后，我们展示了该数据集在多语言环境中训练模型以有效区分虚假信息和可信内容的适用性。