发表机构
HTW Berlin; Goethe University, Frankfurt（柏林工业大学; 法兰克福歌德大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究为阴谋论参与者制定注释指南，构建德语Telegram帖子语料库，用基于Transformer的模型研究自动提取方法，应用于相关档案，能对阴谋叙事中的参与者表征进行大规模分析。
AI 中文摘要
阴谋论通常将重大事件归因于强大且隐秘的参与者的行动。虽然计算研究主要集中在对阴谋论的文档级分析，但较少关注识别推动此类叙事的参与者。我们为阴谋论参与者制定注释指南，展示德语Telegram帖子的跨度注释语料库，并使用基于Transformer的模型研究它们的自动提取。我们进一步将所得模型应用于Schwurbelarchiv，这是一个与德国阴谋相关的Telegram频道的大规模存档。我们的结果表明，尽管阴谋话语的语言复杂性，但阴谋论参与者可以通过有意义的一致性进行注释，并以合理的准确性进行提取，从而能够对阴谋叙事中的参与者表征进行大规模分析。
英文摘要
Conspiracy theories commonly attribute important events to the actions of powerful and secretive actors. While computational research has largely focused on document-level analyses of conspiracy theories, less attention has been paid to identifying the actors that drive such narratives. We develop annotation guidelines for conspiratorial actors, present a span-annotated corpus of German Telegram posts, and investigate their automatic extraction using transformer-based models. We further apply the resulting model to the \textit{Schwurbelarchiv}, a large-scale archive of German conspiracy-related Telegram channels. Our results demonstrate that conspiratorial actors can be annotated with meaningful agreement and extracted with reasonable accuracy despite the linguistic complexity of conspiracy discourse, enabling large-scale analyses of actor representations in conspiracy narratives.
CommentsAccepted to the 6th Workshop on Online Abuse and Harms (WOAH 2026)
