计算机科学与探索2025，Vol.19Issue(4)：1021-1035,15.DOI:10.3778/j.issn.1673-9418.2406053
融合图文多粒度情感特征的多模态谣言检测方法
Multimodal Rumor Detection Method Based on Multi-granularity Emotional Fea-tures of Image-Text
摘要
Abstract
Rumors involving public safety,disasters,and other mass incidents often contain rich emotional features in text or images,which easily mobilize netizens'emotional responses,inducing them to like,comment,and share.However,existing multimodal rumor detection methods lack effective extraction techniques for the emotional features contained in multimodal data and fail to consider the interrelationship between modalities during feature fusion,resulting in redundant and less accurate feature representations.To explore the role of cross-modal emotional features in rumor detection,a multi-modal rumor detection method that integrates multi-granularity emotional features of image-text is proposed.Without relying on social information such as comments and dissemination patterns,this method integrates multi-granularity emotional features into the multimodal rumor detection process.It employs a cross-modal multi-granularity emotional feature fusion method based on an interactive attention mechanism to fully integrate deep features of multimedia information.To evalu-ate the effectiveness of the proposed method,comparative and ablation experiments are conducted on two public datasets,Weibo and Twitter.The results indicate that the proposed method improves rumor detection accuracy to 0.912 on the Wei-bo dataset and 0.839 on the Twitter dataset,showing superior performance across multiple metrics such as F1 value,effec-tively enhancing rumor detection performance and the interpretability of the model.To some extent,it can assist public secu-rity agencies in handling rumors during mass incidents,providing technical support for grassroots police operations.关键词
谣言检测/情感分析/多模态融合/注意力机制/群体性事件Key words
rumor detection/emotional analysis/multimodal fusion/attention mechanism/mass incidents分类
信息技术与安全科学引用本文复制引用
刘先博,向澳,杜彦辉..融合图文多粒度情感特征的多模态谣言检测方法[J].计算机科学与探索,2025,19(4):1021-1035,15.基金项目
中国人民公安大学网络空间安全执法技术双一流创新研究专项(2023SYL07).This work was supported by the Innovative Research Project of Double First-Class in Cybersecurity Law Enforcement Technology at the People's Public Security University of China(2023SYL07). （2023SYL07）
