Short Video is not only Video: Multimodal Unified Social Hypergraph Contrastive Enhancement for Fake News Video Detection
Authors: Mingxin Li, Bohan Qi, Yuchen Zhang, Xianghua Li, Chao Gao, Zhen Wang


Reviewer paper summaries: This paper proposes a Multimodal Unified Social Hypergraph Contrastive Enhancement method (MUHC) for detecting fake news videos. MUHC introduces a unified social hypergraph establishment method for short videos and a multimodal contrastive learning method for intra-modal and inter-modal feature alignment and enhancement. The authors validate the model's performance through experiments on one benchmark dataset.
Summary of strengths: 1. The article addresses the practical issue of fake news detection, which holds significant real-world importance.
2. The authors conducted various experiments to verify the effectiveness of the proposed model.
Summary of weaknesses: 1. The idea of using Graph Representation Learning to aggregate features of related videos within the same event is not novel. The authors need to clearly state the additional highlights of their work compared to previous studies.
2. The experimental dataset is limited to only one. It would be beneficial to include comparative analysis on additional datasets.
3. The authors did not clearly explain some details of their approach, such as the pruning method used.
Comments, suggestions and typos: The paper contains some typos, such as "line 289: a" and "line 302: represent". Correcting these errors is recommended for better clarity.
Overall assessment scores: 2