The widespread dissemination of fake news poses significant harm to individuals and society.To detect fake news in different contexts,this paper incorporates the background factual features and stylistic features of news into the model.This integration enhances the model's ability to detect fake news lacking background knowledge and improves its robustness.The stylistic features include emotional style and textual style.Additionally,this paper con-structs a multi-channel integrator that combines differential features of news and background knowledge,semantic features,and stylistic features,forming the FSFD framework.Validation using the CHEF Chinese open dataset demonstrates that the proposed method outperforms the baseline model by 2.3％in terms of F1 score.
关键词
虚假新闻检测/证据检索/多通道融合/预训练模型
Key words
fake news detection/evidence retrieval/multi-channel fusion/pre-trained model
维普
万方数据