手法を比較

	加重二部ネットワーク分析	加重モジュラリティ分析
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Machine learning
提唱年	1997 (two-mode); weighted extensions 2000s	2004
提唱者	Borgatti, S. P. & Everett, M. G.	Newman, M. E. J.
種類	Network structural analysis	Community structure optimization on weighted graphs
原典	Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269.	Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131.
別名	weighted bipartite network analysis, valued two-mode network analysis, weighted affiliation network analysis, W2MNA	weighted modularity, weighted Q optimization, weighted network community detection, strength-based modularity
関連	6	5
概要	Weighted two-mode network analysis examines bipartite graphs in which two distinct node sets — such as actors and events, authors and papers, or species and habitats — are connected by edges carrying numerical weights that capture the strength, frequency, or intensity of each affiliation. Incorporating weights provides substantially richer structural insights than unweighted bipartite analysis.	Weighted 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.