自动化事实核查中的声明检测：关于单语、多语和跨语言研究的综述
Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Research
AI总结：
本文综述了自动化事实核查中的声明检测研究，聚焦多语言数据与方法，按可验证性、优先级和相似性分类现有研究，并概述多语言数据集、挑战及未来方向。
摘要：
由于在线平台上虚假信息传播的增加，自动化事实核查在过去几十年中引起了广泛关注。这通常作为一系列任务来执行，包括检测在线平台上流传的、构成需要验证的声明的句子，随后是对这些声明的验证过程。本综述聚焦于前者，讨论了在检测需要事实核查的声明方面的现有努力，特别关注多语言数据和方法。这是一个充满挑战且富有前景的方向，由于该问题本质上的极大挑战性，现有方法远未达到人类水平。特别是，信息在多个社交平台上以多种语言和模态进行传播，这要求更具通用性的解决方案来对抗虚假信息。聚焦于多语言虚假信息，我们对现有的多语言声明检测研究进行了全面综述。我们展示了最先进的多语言声明检测研究，并将其按该问题的三个关键因素——可验证性、优先级和相似性——进行分类。此外，我们对现有的多语言数据集及其面临的挑战进行了详细概述，并建议了未来可能的进展。
英文摘要：
Automated fact-checking has drawn considerable attention over the past few decades due to the increase in the diffusion of misinformation on online platforms. This is often carried out as a sequence of tasks comprising (i) the detection of sentences circulating in online platforms which constitute claims needing verification, followed by (ii) the verification process of those claims. This survey focuses on the former, by discussing existing efforts towards detecting claims needing fact-checking, with a particular focus on multilingual data and methods. This is a challenging and fertile direction where existing methods are yet far from matching human performance due to the profoundly challenging nature of the issue. Especially, the dissemination of information across multiple social platforms, articulated in multiple languages and modalities demands more generalized solutions for combating misinformation. Focusing on multilingual misinformation, we present a comprehensive survey of existing multilingual claim detection research. We present state-of-the-art multilingual claim detection research categorized into three key factors of the problem, verifiability, priority, and similarity. Further, we present a detailed overview of the existing multilingual datasets along with the challenges and suggest possible future advancements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
