Poster: Leveraging Question Answering to Understand Context Specific Patterns in Fact Checked Articles in the Global South

Arshia Arya, Saloni Dash, Syeda Zainab Akbar, J. Pal, Anirban Sen
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引用次数: 0

Abstract

Propagation of misinformation on various social media platforms is a common occurrence, especially around political events, religious beliefs, and public health. Fact checked articles, which investigate the credibility of dubious claims online, provide a reliable source of debunked misinformation. However, existing (older) fact checked articles remain an underutilized resource for understanding patterns in fake stories. We propose the use of Question Answering (QA) for analysing fact checked articles for systematically extracting metadata, potentially useful for downstream tasks such as misinformation detection, using a range of simple to nuanced questions. We find that the method gives us a context-specific understanding of common patterns and themes in misinformation, which is especially important in the Global South, where misinformation is layered with propagandist underpinning. Our findings suggest that this method can be extended by fine tuning on any event specific data set of fact checked articles to yield more robust and accurate results.
海报:利用问答来理解南半球事实核查文章的上下文特定模式
在各种社交媒体平台上传播错误信息是一种常见现象,特别是在政治事件、宗教信仰和公共卫生方面。事实核查文章调查网上可疑言论的可信度,为揭穿错误信息提供了可靠来源。然而,现有的(较旧的)事实核查文章仍然是一种未充分利用的资源,用于理解假故事的模式。我们建议使用问答(QA)来分析事实验证文章,以系统地提取元数据,这对于下游任务(如错误信息检测)可能有用,使用一系列简单到细微的问题。我们发现,该方法使我们对错误信息的常见模式和主题有了具体的理解,这在全球南方尤其重要,在那里,错误信息被宣传主义者所支撑。我们的研究结果表明,这种方法可以通过对事实检查文章的任何事件特定数据集进行微调来扩展,以产生更健壮和准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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