Methoden vergleichen

	Betweenness-Zentralität	Eigenvektor-Zentralität
Fachgebiet	Netzwerkanalyse	Netzwerkanalyse
Familie	Machine learning	Machine learning
Entstehungsjahr	1977	1972
Urheber	Freeman, L. C.	Bonacich, P.
Typ	Centrality measure	Centrality measure
Wegweisende Quelle	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.	Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120.
Aliasnamen	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness	eigenvector centrality, EC, Bonacich centrality, power centrality
Verwandt	6	6
Zusammenfassung	Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes.	Eigenvector centrality, introduced by Bonacich in 1972, measures a node's influence by considering not just how many neighbors it has, but how influential those neighbors are. A node scores highly if it is connected to other high-scoring nodes, making it a recursive, globally-aware measure of structural importance in a network.