Node embedding is a technique that maps each vertex of a graph to a low-dimensional vector such that structural relationships in the graph, such as proximity, connectivity, or community membership, are preserved as geometric relationships in the embedding space. Methods range from random-walk based approaches to graph neural network encoders that aggregate information from a node’s neighbourhood. Node embeddings support downstream tasks such as community detection, link prediction, and node classification.