Real-Time Detection of Misinformation Influencers

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This research explores misinformation propagation and the role of shadow influencers, addressing the limitations of static centrality and snapshot-based GNNs. It reviews dynamic graph learning and identifies gaps in existing methodologies like ROLAND and DDGCN, emphasizing the need for continuous-time evaluations. The proposed Continuous-Time Graph-NLP Fusion Framework integrates asynchronous multimodal data ingestion and employs GRU for memory updates, culminating in an influence-risk...