Eigenvector centrality

In graph theory, eigenvector centrality (also called eigencentrality or prestige score) is a measure of the influence of a node in a connected network. Relative scores are assigned to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes. A high eigenvector score means that a node is connected to many nodes who themselves have high scores.

Google's PageRank and the Katz centrality are variants of the eigenvector centrality.