Methoden vergelijken

	Betweenness Centrality	Modularity Analysis
Vakgebied	Netwerkanalyse	Netwerkanalyse
Familie	Machine learning	Machine learning
Jaar van ontstaan	1977	2004
Grondlegger	Freeman, L. C.	Newman, M. E. J. & Girvan, M.
Type	Centrality measure	Community detection / graph partitioning
Oorspronkelijke bron	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.	Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.
Aliassen	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness	Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity
Verwant	6	5
Samenvatting	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.	Modularity analysis is a network science method, formalized by Newman and Girvan in 2004, that detects community structure in graphs by measuring whether edges are more concentrated within groups than expected by chance. Its scalar quality index Q guides algorithms that partition nodes into cohesive clusters, making it the most widely adopted framework for community detection in social, biological, and technological networks.