Comparer des méthodes

	Analyse bayésienne de réseaux bi-modaux	Analyse de réseaux bipartis pondérés
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	1997–2010s	1997 (two-mode); weighted extensions 2000s
Auteur d'origine	Borgatti & Everett (two-mode SNA); Bayesian extensions by multiple authors	Borgatti, S. P. & Everett, M. G.
Type	Probabilistic network model	Network structural analysis
Source fondatrice	Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269.	Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269.
Alias	Bayesian bipartite network analysis, probabilistic two-mode network analysis, Bayesian affiliation network analysis, Bayesian two-mode SNA	weighted bipartite network analysis, valued two-mode network analysis, weighted affiliation network analysis, W2MNA
Apparentées	5	6
Résumé	Bayesian two-mode network analysis applies probabilistic Bayesian inference to bipartite (two-mode) networks — graphs linking two distinct sets of nodes such as actors and events, authors and papers, or consumers and products. By placing priors over tie probabilities and structural parameters, analysts obtain uncertainty estimates around centrality, community membership, and projection metrics rather than single-point estimates.	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.