The full-scale conflict between the Russian Federation and Ukraine generated
an unprecedented amount of news articles and social media data reflecting
opposing ideologies and narratives. These polarized campaigns have led to
mutual accusations of misinformation and fake news, shaping an atmosphere of
confusion and mistrust for readers worldwide. This study analyses how the media
affected and mirrored public opinion during the first month of the war using
news articles and Telegram news channels in Ukrainian, Russian, Romanian and
English. We propose and compare two methods of multilingual automated
pro-Kremlin propaganda identification, based on Transformers and linguistic
features. We analyse the advantages and disadvantages of both methods, their
adaptability to new genres and languages, and ethical considerations of their
usage for content moderation. With this work, we aim to lay the foundation for
further development of moderation tools tailored to the current conflict.

本研究使用新闻文章和 Telegram 新闻频道在乌克兰、俄罗斯、罗马尼亚和英语中分析了战争第一个月期间媒体对公众舆论的影响和反映，并提出并比较了两种基于 Transformer 和语言特征的多语言自动化亲俄罗斯宣传识别方法，分析了它们的优缺点，适用于新的流派和语言，并对其用于内容管理的道德问题进行了分析，旨在为针对当前冲突量身定制的管理工具的进一步发展奠定基础。

自动多语言检测报纸和 Telegram 帖子中的亲克里姆林宫宣传

Automated multilingual detection of Pro-Kremlin propaganda in newspapers and Telegram posts

Our lives are ruled by events of varying importance ranging from simple
everyday occurrences to incidents of societal dimension. And a lot of effort is
taken to exchange information and discuss about such events: generally
speaking, stringent narratives are formed to reduce complexity. But when
considering complex events like the current conflict between Russia and Ukraine
it is easy to see that those events cannot be grasped by objective facts alone,
like the start of the conflict or respective troop sizes. There are different
viewpoints and assessments to consider, a different understanding of the roles
taken by individual participants, etc. So how can such subjective and
viewpoint-dependent information be effectively represented together with all
objective information? Recently event-centric knowledge graphs have been
proposed for objective event representation in the otherwise primarily
entity-centric domain of knowledge graphs. In this paper we introduce a novel
and lightweight structure for event-centric knowledge graphs, which for the
first time allows for queries incorporating viewpoint-dependent and narrative
aspects. Our experiments prove the effective incorporation of subjective
attributions for event participants and show the benefits of specifically
tailored indexes for narrative query processing.

本文提出了一种新颖而轻量级的事件中心知识图谱结构，允许查询包括视角依赖和叙事方面，并证明了主观归属的有效结合，展示了为叙事查询处理专门定制的索引的好处。