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Dynamic Community Detection/Evidence
Method evidence record

Dynamic Community Detection

Dynamic community detection identifies groups of densely connected nodes in networks that evolve over time, tracking how communities form, merge, split, and dissolve across temporal snapshots. Developed to extend static modularity optimization to time-varying structures, it is widely used in social, biological, and communication network research.

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Source record

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

Dynamic Community Detection in Evolving Networks
Taxonomic method record · ml-model / network-analysis
  • 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
  • Fortunato, S., & Hric, D. (2016). Community detection in networks: A user guide. Physics Reports, 659, 1–44. · DOI 10.1016/j.physrep.2016.09.002
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Curated claims

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