Predicting New Adopters Via Socially-Aware Neural Graph Collaborative Filtering

We predict new adopters of specific items by proposing SNGCF, a socially-aware neural graph collaborative filtering model. This model uses information about social influence and item adoptions; then it learns the representation of user-item relationships via a graph convolutional network. Experiments show that social influence is essential for adopter prediction. S-NGCF outperforms the prediction of new adopters compared to state-of-the-art methods by 18%.