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Multilayer Community Detection/Evidence
Method evidence record

Multilayer Community Detection

Multilayer community detection identifies groups of nodes that are densely connected across multiple types of relationships simultaneously. By coupling layers of a network — such as friendship, advice, and collaboration ties — it finds communities that are coherent not just within one relation type but across all of them, revealing structure that single-layer analysis would miss.

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Source record

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

Multilayer Community Detection in Multiplex and Multilayer Networks
Taxonomic method record · ml-model / network-analysis
  • Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. · DOI 10.1093/comnet/cnu016
  • Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876–878. · DOI 10.1126/science.1184819
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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.

Used in the same domainCommunity Detectionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketModularity Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMultilayer Social Network Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMultiplex Network Analysismachine-suggested · Relational suggestion, not evidence.Used in the same domainStochastic Block Modelmachine-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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