Social Network Analysis Based on Graph SAGE

Social network node classification has important application value in real life. Traditional iterative application classifiers and random walk based tag propagation algorithms do not fully consider the interaction information between nodes. Graphsage is an effective graph neural network model that can be used for social network analysis. This paper uses the graphsage model to analyze social networks, compares them with traditional social network analysis methods, discusses the values of some parameters of the model, and makes some improvements in the model sampling part.