论文标题
对事实核对的主张太多：基于校验值的政治主张优先考虑
Too Many Claims to Fact-Check: Prioritizing Political Claims Based on Check-Worthiness
论文作者
论文摘要
每天在互联网上传播的大量错误信息对社会产生了巨大的负面影响。因此，我们需要自动化系统，以帮助核对事实检查者进行战斗，以防止错误信息。在本文中，我们提出了一个模型，根据索赔的质疑优先级。我们将BERT模型带有其他功能，包括特定于域的有争议的主题，单词嵌入等。在我们的实验中，我们表明我们提出的模型在CLEF的两个测试集中都优于所有最新模型，请检查！在2018年和2019年的实验室。我们还进行了定性分析，以示出值得检测的值得检查的主张。我们建议需要判断背后的理由来了解任务和有问题的标签的主观性质。
The massive amount of misinformation spreading on the Internet on a daily basis has enormous negative impacts on societies. Therefore, we need automated systems helping fact-checkers in the combat against misinformation. In this paper, we propose a model prioritizing the claims based on their check-worthiness. We use BERT model with additional features including domain-specific controversial topics, word embeddings, and others. In our experiments, we show that our proposed model outperforms all state-of-the-art models in both test collections of CLEF Check That! Lab in 2018 and 2019. We also conduct a qualitative analysis to shed light-detecting check-worthy claims. We suggest requesting rationales behind judgments are needed to understand subjective nature of the task and problematic labels.
