방법 비교

	Betweenness Centrality	모듈성 분석
분야	네트워크 분석	네트워크 분석
계열	Machine learning	Machine learning
기원 연도	1977	2004
창시자	Freeman, L. C.	Newman, M. E. J. & Girvan, M.
유형	Centrality measure	Community detection / graph partitioning
원전	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.
별칭	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness	Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity
관련	6	5
요약	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.