Editing Network theory (section)

===Centrality measures===
Information about the relative importance of nodes and edges in a graph can be obtained through [[centrality]] measures, widely used in disciplines like [[sociology]]. For example, [[eigenvector centrality]] uses the [[eigenvectors]] of the [[adjacency matrix]] corresponding to a network, to determine nodes that tend to be frequently visited. Formally established measures of centrality are [[degree centrality]], [[closeness centrality]], [[betweenness centrality]], [[eigenvector centrality]], [[subgraph centrality]], and [[Katz centrality]]. The purpose or objective of analysis generally determines the type of centrality measure to be used. For example, if one is interested in dynamics on networks or the robustness of a network to node/link removal, often the [[dynamical importance]]<ref>{{cite journal | vauthors = Restrepo JG, Ott E, Hunt BR | title = Characterizing the dynamical importance of network nodes and links | journal = Physical Review Letters | volume = 97 | issue = 9 | pages = 094102 | date = September 2006 | pmid = 17026366 | doi = 10.1103/PhysRevLett.97.094102 | arxiv = cond-mat/0606122 | s2cid = 18365246 | bibcode = 2006PhRvL..97i4102R }}</ref>  of a node is the most relevant centrality measure.