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Centralidad de Intermediación Multicapa×Detección de comunidades multicapa×
CampoAnálisis de redesAnálisis de redes
FamiliaMachine learningMachine learning
Año de origen2013–20142010–2014
Autor originalDe Domenico, M.; Kivelä, M.; Arenas, A. et al.Mucha, P. J. et al.; Kivela, M. et al.
TipoCentrality measure (multilayer extension)Community detection algorithm for multilayer networks
Fuente seminalDe Domenico, M., Solé-Ribalta, A., Cozzo, E., Kivelä, M., Moreno, Y., Porter, M. A., Gómez, S., & Arenas, A. (2013). Mathematical formulation of multilayer networks. Physical Review X, 3(4), 041022. DOI ↗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 ↗
AliasMBC, multilayer geodesic betweenness, tensorial betweenness centrality, interlayer betweenness centralitymultilayer clustering, multiplex community detection, cross-layer community detection, MCD
Relacionados55
ResumenMultilayer betweenness centrality extends the classical betweenness measure to networks with multiple types of relationships — or layers — by computing how often a node lies on shortest paths that can traverse any layer or switch between layers. It identifies brokers and bridges whose influence spans distinct interaction domains simultaneously.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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ScholarGateComparar métodos: Multilayer Betweenness Centrality · Multilayer Community Detection. Recuperado el 2026-06-17 de https://scholargate.app/es/compare