HC-COVID

The proliferation of social media has promoted the spread misinformation that raises many concerns in our society. This paper focuses on a critical problem explainable COVID-19 detection aims to accurately identify and explain misleading claims media. Motivated by lack relevant knowledge existing solutions, we construct novel crowdsource graph based approach incorporate facts leveraging collaborative efforts expert non-expert crowd workers. Two important challenges exist developing solution: i) how effectively coordinate from both workers generate for detecting misinformation; ii) How leverage constructed detected misinformation. To address above challenges, develop HC-COVID, hierarchical framework explicitly models contributed with different levels expertise identifies related results. We evaluate HC-COVID using two public real-world datasets Evaluation results demonstrate significantly outperforms state-of-the-art baselines terms accuracy quality explanations.