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Fact-Checking Meets Fauxtography: Verifying Claims About Images

机译:事实核查与人工成像:验证有关图像的声明

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摘要

The recent explosion of false claims in social media and on the Web in general has given rise to a lot of manual fact-checking initiatives. Unfortunately, the number of claims that need to be fact-checked is several orders of magnitude larger than what humans can handle manually. Thus, there has been a lot of research aiming at automating the process. Interestingly, previous work has largely ignored the growing number of claims about images. This is despite the fact that visual imagery is more influential than text and naturally appears alongside fake news. Here we aim at bridging this gap. In particular, we create a new dataset for this problem, and we explore a variety of features modeling the claim, the image, and the relationship between the claim and the image. The evaluation results show sizable improvements over the baseline. We release our dataset. hoping to enable further research on fact-checking claims about images.
机译:社交媒体和整个Web上最近虚假声明的激增,引发了许多手动的事实检查计划。不幸的是,需要事实检查的索赔数量比人类可以手动处理的索赔数量大几个数量级。因此,已经有许多旨在使过程自动化的研究。有趣的是,以前的工作在很大程度上忽略了关于图像的越来越多的主张。尽管存在这样的事实,即视觉图像比文本更具影响力,并且自然会与假新闻一起出现。在这里,我们旨在弥合这一差距。特别是,我们针对此问题创建了一个新的数据集,并探索了对索赔,图像以及索赔与图像之间的关系进行建模的各种功能。评估结果显示,与基准相比有了很大的改进。我们发布数据集。希望能够对有关图像的事实检查声明进行进一步的研究。

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