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	Analýza časovej modularity	Vážená analýza modularity
Odbor	Analýza sietí	Analýza sietí
Rodina	Machine learning	Machine learning
Rok vzniku	2010	2004
Tvorca	Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P.	Newman, M. E. J.
Typ	Community detection (temporal extension of modularity optimization)	Community structure optimization on weighted graphs
Pôvodný zdroj	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.	Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131.
Ďalšie názvy	dynamic modularity, time-varying modularity, longitudinal community detection, temporal community structure analysis	weighted modularity, weighted Q optimization, weighted network community detection, strength-based modularity
Príbuzné	5	5
Zhrnutie	Temporal modularity analysis extends standard modularity-based community detection to time-varying networks by treating each time slice as a network layer and coupling adjacent layers with inter-temporal links. This allows researchers to identify how communities form, persist, merge, split, and dissolve over time in dynamic relational data.	Weighted modularity analysis extends the classical Newman-Girvan modularity measure to networks where edges carry numeric strengths (frequencies, intensities, costs). By replacing binary adjacency with tie weights, it finds community partitions that reflect how densely interconnected subgroups are relative to what is expected under a weighted null model, yielding more nuanced groupings than unweighted approaches on data where edge strength varies meaningfully.