福建师范大学学报（自然科学版）2025，Vol.41Issue(2)：43-54,116,13.DOI:10.12046/j.issn.1000-5277.2024030063
域视角下基于深度学习的虚假新闻检测方法
Deep Learning for Fake News Detection Based on a Domain Perspective
摘要
Abstract
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.关键词
虚假新闻检测/深度学习/域视角/人工智能Key words
fake news detection/deep learning/domain perspective/artificial intelligence分类
信息技术与安全科学引用本文复制引用
陈烁淳,黄发良,戴智鹏,黄恩博..域视角下基于深度学习的虚假新闻检测方法[J].福建师范大学学报（自然科学版）,2025,41(2):43-54,116,13.基金项目
国家自然科学基金项目(62262045) （62262045）
广西重点研发计划项目(桂科AB22035072) （桂科AB22035072）
