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Fake News Detection Based on Cross-modal Message Aggregation and Gated Fusion Network

Computers, Materials & Continua 2024年第7期80卷 1521-1542页

作者： Fangfang Shan Mengyao Liu Menghan Zhang Zhenyu Wang College of Computer Zhongyuan University of TechnologyZhengzhou450007China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001China

Social media has become increasingly significant in modern society,but it has also turned into a breeding ground for the propagation of misleading information,potentially causing a detrimental impact on public opinion and daily *** to pure text content,multmodal content significantly increases the visibility and share ability of *** has made the search for efficient modality representations and cross-modal information interaction methods a key focus in the field of multimodal fake news *** effectively address the critical challenge of accurately detecting fake news on social media,this paper proposes a fake news detection model based on crossmodal message aggregation and a gated fusion network(MAGF).MAGF first uses BERT to extract cumulative textual feature representations and word-level features,applies Faster Region-based ConvolutionalNeuralNetwork(Faster R-CNN)to obtain image objects,and leverages ResNet-50 and Visual Geometry Group-19(VGG-19)to obtain image region features and global *** image region features and word-level text features are then projected into a low-dimensional space to calculate a text-image affinity matrix for cross-modal message *** gated fusion network combines text and image region features to obtain adaptively aggregated *** interaction matrix is derived through an attention mechanism and further integrated with global image features using a co-attention mechanism to producemultimodal ***,these fused features are fed into a classifier for news *** were conducted on two public datasets,Twitter and *** show that the proposed model achieves accuracy rates of 91.8%and 88.7%on the two datasets,respectively,significantly outperforming traditional unimodal and existing multimodal models.

关键词： Fake news detection cross-modalmessage aggregation gate fusion network co-attention mechanism multi-modal representation

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