Methoden vergleichen

	Eigenvektor-Zentralität	Betweenness-Zentralität
Fachgebiet	Netzwerkanalyse	Netzwerkanalyse
Familie	Machine learning	Machine learning
Entstehungsjahr	1972	1977
Urheber	Bonacich, P.	Freeman, L. C.
Typ	Centrality measure	Centrality measure
Wegweisende Quelle	Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120.	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.
Aliasnamen	eigenvector centrality, EC, Bonacich centrality, power centrality	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness
Verwandt	6	6
Zusammenfassung	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.	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.