%0 Journal Article
%A JIANG Ya-fei
%A LIU Yong-bin
%A XIE Yang
%A LI Lei
%T A Social Relationship Direction Gating Algorithm for Graph Convolutional Networks
%D 
%R 10.13190/j.jbupt.2020-074
%J Journal of Beijing University of Posts and Telecommunications
%P 77-83
%V 43
%N 5
%X Facing the problem in social user attitude analysis that the original social relationship direction between users in social networks hinders the flow of attitude information and label propagation, a social relationship direction gating algorithm for graph convolutional networks is proposed. The algorithm first performs graph convolution on the origin and reverse social relationship directions to obtain two types of user node attitude feature vectors, and then leverages the gating mechanism to integrate the feature vectors dynamically. While expanding the propagation of attitude information, the algorithm can also capture the differences of user influence to automatically select the flow of attitude information. Experiments on two real hot topic datasets show that the accuracy of the existing graph convolutional networks can be effectively improved after adding the proposed algorithm.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2020-074