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Bayesian Two-Mode Network Analysis

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.

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  1. Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269. DOI: 10.1016/S0378-8733(96)00301-2
  2. Latouche, P., Birmele, E., & Ambroise, C. (2011). Overlapping stochastic block models with application to the French political blogosphere. Annals of Applied Statistics, 5(1), 309–336. DOI: 10.1214/10-AOAS382

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ScholarGate. (2026, June 3). Bayesian Two-Mode (Bipartite) Network Analysis. ScholarGate. https://scholargate.app/et/network-analysis/bayesian-two-mode-network-analysis

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ScholarGateBayesian Two-Mode Network Analysis (Bayesian Two-Mode (Bipartite) Network Analysis). Loetud 2026-06-15 aadressilt https://scholargate.app/et/network-analysis/bayesian-two-mode-network-analysis · Andmestik: https://doi.org/10.5281/zenodo.20539026