Bandingkan metode

	Analisis Jaringan Dua-Moda Berbobot	Analisis Modulitas Tertimbang
Bidang	Analisis Jaringan	Analisis Jaringan
Keluarga	Machine learning	Machine learning
Tahun asal	1997 (two-mode); weighted extensions 2000s	2004
Pencetus	Borgatti, S. P. & Everett, M. G.	Newman, M. E. J.
Tipe	Network structural analysis	Community structure optimization on weighted graphs
Sumber perintis	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.
Alias	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
Terkait	6	5
Ringkasan	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.