在线讨论的计算事实核查：在气候变化相关新闻文章中评估科学准确性
Computational Fact-Checking of Online Discourse: Scoring scientific accuracy in climate change related news articles
AI总结：
本文提出了一种半自动化的在线讨论事实核查方法，通过知识图谱分析评估气候变化相关新闻文章的科学准确性，并指出需要进一步完善事实知识图谱以支持科学公民讨论。
摘要：
民主社会需要可靠的信息。流行媒体中的错误信息，如新闻文章或视频，可能损害公民讨论。不幸的是，公民无法验证日益增加的每日内容流。本工作旨在半自动化地量化在线媒体的科学准确性。我们调查了与气候变化相关的事实知识表示的最新状态。通过语义化不可靠的媒体内容，其陈述可以与这些事实知识图谱进行比较。我们实现了使用基于LLM的陈述提取和知识图谱分析的工作流程。我们的实现可以将内容处理流程推进到最先进的知识表示和真实性量化。在27名专家的帮助下开发和评估，并通过10次详细访谈，该工具显然提供了有益的真实性指示。这些发现得到了43名匿名参与者的平行用户调查的支持。然而，这一步无法在所需粒度和规模上标注公共媒体。此外，识别出的气候变化知识图谱状态远不足以支持这种神经符号事实核查方法。需要进一步的工作以支持科学的公民讨论，包括FAIR（可找到、可访问、可互操作、可重用）的事实和互补的度量标准。
英文摘要：
Democratic societies need reliable information. Misinformation in popular media, such as news articles or videos, threatens to impair civic discourse. Citizens are, unfortunately, not equipped to verify the flood of content consumed daily at increasing rates. This work aims to quantify the scientific accuracy of online media semi-automatically. We investigate the state of the art of climate-related ground truth knowledge representation. By semantifying media content of unknown veracity, their statements can be compared against these ground truth knowledge graphs. We implemented a workflow using LLM-based statement extraction and knowledge graph analysis. Our implementation can streamline content processing towards state-of-the-art knowledge representation and veracity quantification. Developed and evaluated with the help of 27 experts and detailed interviews with 10, the tool evidently provides a beneficial veracity indication. These findings are supported by 43 anonymous participants from a parallel user survey. This initial step, however, is unable to annotate public media at the required granularity and scale. Additionally, the identified state of climate change knowledge graphs is vastly insufficient to support this neurosymbolic fact-checking approach. Further work towards a FAIR (Findable, Accessible, Interoperable, Reusable) ground truth and complementary metrics is required to support civic discourse scientifically.
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。
