Before revision:  We employ two distinct exploring layers including a self-attention layer and a similarity calculation layer to fully consider the users' intimacy across different relationships, and a following fusion layer based on graph convolution network(GCN) to consolidate the similarity and enhance the node embedding . We evaluate our proposed model with real-world datasets and results show our approach can achieve over 90\% accuracy for user classification, far better than other comparable baselines .
After revision:  We employ two distinct exploring layers including a self-attention layer and a similarity calculation layer to fully consider the users' intimacy across different relationships, and a following fusion layer based on graph convolution network(GCN) to consolidate the node embedding by aggregating the final users' embeddings. We conduct extensive experiment on real-world datasets and results show our approach can achieve over 90\% accuracy for user classification, far better than other comparable baselines .