A graph neural network-based node classification method, during training of a model, categories of a plurality of neighboring node samples in a graph data sample are first predicted to obtain category distribution of the plurality of neighboring node samples, and sampling is then performed on the plurality of neighboring node samples based on the category distribution and a sampling parameter input by a user to obtain a plurality of sampled nodes, so that category distribution of the plurality of sampled nodes is similar to or consistent with the category distribution of the plurality of neighboring node samples.