Information Diffusion Prediction via Dynamic Graph Neural Networks

GCNFusion: An efficient graph convolutional network based model for information diffusion

“…(Z. Cao et al, 2021) Deep learning -GNN GCNFusion Hybrid SIR GCN to obtain representation vectors using both topological and feature information, DGI (Velickovic et al, 2019) uses a mutual information maximization strategy to learn node representation vectors, MAPPING (Fatemi, Molaei, Zare, & Pan, 2021) obtains node representation vectors aggregating graph neural networks with a manifold learning algorithm.…”

“…Information diffusion is a genuinely interdisciplinary topic to the extent that researchers from various disciplines, including computer science, social sciences, political sciences, and medical sciences, etc have been seriously pursuing it (Z. Cao, Han, & Zhu, 2021;X. Chen et al, 2019;Qi, Li, Chen, & Xue, 2021;H.…”