• Published 2019

Cascade 2 vec : Learning Dynamic Cascade Representation by Recurrent Graph Neural Networks

@inproceedings{Huang2019Cascade2V,
  title={Cascade 2 vec : Learning Dynamic Cascade Representation by Recurrent Graph Neural Networks},
  author={Zhenhua Huang and Zhen-yu Wang and Rui Zhang},
  year={2019}
}
An information dissemination network (i.e., a cascade) with a dynamic graph structure is formed when a novel idea or message spreads from person to person. Predicting the growth of cascades is one of the fundamental problems in social network analysis. Existing deep learning models for cascade prediction are primarily based on recurrent neural networks and representation on random walks or propagation paths. However, these models are not sufficient for learning the deep spatial and temporal… CONTINUE READING

References

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DAGCN: Dual Attention Graph Convolutional Networks