In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language inference methods with a self-attention network, outperforms state-of-the-art approaches. It is also able to give automated veracity assessment and ranked supporting evidence with the stance towards the claim to be checked. In addition, PANACEA adapts the bi-directional graph convolutional networks model, which is able to detect rumours based on comment networks of related tweets, instead of relying on the knowledge base. This rumour detection module assists by warning the users in the early stages when a knowledge base may not be available.
翻译:在这一演示中,我们引入了一个基于网络的错误信息检测系统,即PANACEA系统,该系统涉及COVID-19(COVID-19)相关索赔,它有两个模块,即事实核查和谣言探测。我们的事实检查模块,由具有自我关注网络的新型自然语言推断方法支持,它优于最先进的方法。它还能够自动进行真实性评估,并将支持性证据与要求检验的立场排列为等级。此外,PANACEA还调整双向图形共变网络模型,该模型能够根据相关推文的评论网络发现谣言,而不是依赖知识基础。这个信号检测模块协助在可能没有知识基础的早期阶段向用户发出警告。</s>