域视角下基于深度学习的虚假新闻检测方法OA北大核心

This paper follows the development of deep learning to classify fake news detection models from a domain perspective and examineses the evolution of detection methods First,the over-view introduces the definition of fake news detection from a domain perspective,domain-specific datasets,evaluation metrics for fake news detection,and related work.Then,based on the domain perspective,fake news detection models are categorized into three types:those with the same source and target domains,those with different source and target domains,and those ignoring domain in-formation.These three types of models are systematically reviewed with a focus on deep learning.