A graph centrality is a function that assigns scores to the vertices, edges, or other parts of a graph in order to measure their structural importance. Different centrality measures formalize different notions of importance, such as having many incident edges, being close to other vertices, lying on many shortest paths, or being adjacent to important vertices.
Graph centrality measures are used in areas such as social network analysis, communication networks, web search, and community detection.
Centrality measures for named graphs are available through properties such as GraphData[graph, "BetweennessCentralities"], GraphData[graph, "ClosenessCentralities"], and GraphData[graph, "EigenvectorCentralities"].
