Methoden vergelijken

	Bayesiaanse Twee-Modale Netwerkanalyse	Gewogen tweemode-netwerkanalyse
Vakgebied	Netwerkanalyse	Netwerkanalyse
Familie	Machine learning	Machine learning
Jaar van ontstaan	1997–2010s	1997 (two-mode); weighted extensions 2000s
Grondlegger	Borgatti & Everett (two-mode SNA); Bayesian extensions by multiple authors	Borgatti, S. P. & Everett, M. G.
Type	Probabilistic network model	Network structural analysis
Oorspronkelijke bron	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.
Aliassen	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
Verwant	5	6
Samenvatting	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.