Bandingkan kaedah

	Analisis Rangkaian Dua-Mod Diberat	Analisis Modularitas Berbobot
Bidang	Analisis Rangkaian	Analisis Rangkaian
Keluarga	Machine learning	Machine learning
Tahun asal	1997 (two-mode); weighted extensions 2000s	2004
Pengasas	Borgatti, S. P. & Everett, M. G.	Newman, M. E. J.
Jenis	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
Berkaitan	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.