Causal GraphSAGE: A robust graph method for classification based on causal sampling

•Introduces causal inference into GraphSAGE to improve the robustness of GraphSAGE's classification performance.•Proposes a novel causal sampling algorithm using causal bootstrap weights of the neighborhood of a node. Compared with the original uniform random sampling of GraphSAGE, the nodes obtained by such causal sampling select the most robust neighbors for the subsequent aggregation operation.•Causal sampling focuses not only on the structure around the target node, but also on the structural characteristics of neighbors and their labels, making the embedding of nodes in Causal-GraphSAGE more robust.