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Bayesian Community Detection/Evidence
Method evidence record

Bayesian Community Detection

Bayesian community detection infers latent group structure in networks by treating community membership as unobserved variables and using Bayesian inference — typically via Markov chain Monte Carlo or variational methods — to compute a posterior distribution over all plausible partitions. Unlike modularity optimisation, it selects the number of communities from data and provides principled uncertainty estimates for every node assignment.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Bayesian Community Detection in Networks
Taxonomic method record · ml-model / network-analysis
  • Peixoto, T. P. (2014). Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models. Physical Review E, 89(1), 012804. · DOI 10.1103/PhysRevE.89.012804
  • Nowicki, K. & Snijders, T. A. B. (2001). Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association, 96(455), 1077–1087. · DOI 10.1198/016214501753208735
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketModularity Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMultilayer Community Detectionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSocial Network Analysismachine-suggested · Relational suggestion, not evidence.Used in the same domainStochastic Block Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTemporal Community Detectionmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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