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Analyse gerichteter Multiplex-Netzwerke×Gerichtete Gemeinschaftserkennung×
FachgebietNetzwerkanalyseNetzwerkanalyse
FamilieMachine learningMachine learning
Entstehungsjahr2013–20142008
UrheberKivela, M.; De Domenico, M. et al.Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
TypMulti-layer directed graph frameworkGraph partitioning / modularity optimization
Wegweisende QuelleKivela, 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 ↗Leicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703. DOI ↗
Aliasnamendirected multilayer network analysis, directed multiplex graphs, asymmetric multiplex network analysis, DMNAdirected graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
Verwandt66
ZusammenfassungDirected multiplex network analysis models systems where the same set of nodes are connected by multiple types of directed (asymmetric) relationships across distinct layers — such as citation flows, information cascades, or authority hierarchies co-existing simultaneously. It extends multiplex network analysis by preserving both layer identity and edge directionality, enabling richer structural and dynamic insights.Directed community detection identifies densely interconnected groups of nodes in a directed network, accounting for the asymmetry of edges (e.g., A follows B does not imply B follows A). Adapting modularity or flow-based criteria to directed graphs reveals clusters that undirected methods systematically miss, making it essential for citation networks, follower graphs, and biological regulatory pathways.
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ScholarGateMethoden vergleichen: Directed Multiplex Network Analysis · Directed Community Detection. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare