centrality
Sign in to saveIn graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, super-spreaders of disease, and brain networks. Centrality concepts were first developed in social network analysis, and many of the terms used to measure centrality reflect their sociological origin. Over time, the concept has expanded substantially, leading to the development of hundreds of distin
Article
22 sectionsContents
- Definition and characterization of centrality indices
- Characterization by network flows
- Characterization by walk structure
- Radial-volume centralities exist on a spectrum
- Game-theoretic centrality
- Important limitations
- Degree centrality
- Closeness centrality
- Harmonic centrality
- Betweenness centrality
- Eigenvector centrality
- Using the adjacency matrix to find eigenvector centrality
- Katz centrality
- PageRank centrality
- Percolation centrality
- Cross-clique centrality
- Freeman centralization
- Dissimilarity-based centrality measures
- Centrality measures used in transportation networks
- See also
- Notes and references
- Further reading
In graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, super-spreaders of disease, and brain networks. Centrality concepts were first developed in social network analysis, and many of the terms used to measure centrality reflect their sociological origin. Over time, the concept has expanded substantially, leading to the development of hundreds of distinct centrality measures, the most comprehensive listing of which is documented in the CentralityZoo online catalogue.
==Definition and characterization of centrality indices== Centrality indices are answers to the question "What characterizes an important vertex?" The answer is given in terms of a real-valued function on the vertices of a graph, where the values produced are expected to provide a ranking which identifies the most important nodes.