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가중 모듈성 분석×Betweenness Centrality×
분야네트워크 분석네트워크 분석
계열Machine learningMachine learning
기원 연도20041977
창시자Newman, M. E. J.Freeman, L. C.
유형Community structure optimization on weighted graphsCentrality measure
원전Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131. DOI ↗Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗
별칭weighted modularity, weighted Q optimization, weighted network community detection, strength-based modularityFreeman betweenness, BC, geodesic betweenness, shortest-path betweenness
관련56
요약Weighted modularity analysis extends the classical Newman-Girvan modularity measure to networks where edges carry numeric strengths (frequencies, intensities, costs). By replacing binary adjacency with tie weights, it finds community partitions that reflect how densely interconnected subgroups are relative to what is expected under a weighted null model, yielding more nuanced groupings than unweighted approaches on data where edge strength varies meaningfully.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.
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