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Sentralitas Derajat Multilapis×Sentralitas Derajat Berbobot×
BidangAnalisis JaringanAnalisis Jaringan
KeluargaMachine learningMachine learning
Tahun asal2013–20142004
PencetusKivelä, M.; De Domenico, M. et al.Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.
TipeCentrality measure for multilayer networksCentrality measure for weighted networks
Sumber perintisKivelä, 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 ↗Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI ↗
Aliasmultilayer degree, multiplex degree centrality, overlapping-layer degree centrality, MDCnode strength, strength centrality, weighted node degree, WDC
Terkait66
RingkasanMultilayer degree centrality extends the classic degree centrality measure to networks composed of multiple layers — such as networks representing different types of social ties, communication channels, or relationship contexts simultaneously. It quantifies how many connections a node has across one or all layers, revealing nodes that are influential not just in a single context but across the entire multi-relational structure.Weighted degree centrality — also called node strength — extends the classic degree centrality measure to networks whose edges carry numeric weights. Instead of simply counting a node's connections, it sums the weights of all edges incident to that node, capturing both the volume and the intensity of a node's ties in a single, interpretable score.
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ScholarGateBandingkan metode: Multilayer Degree Centrality · Weighted Degree Centrality. Diakses 2026-06-19 dari https://scholargate.app/id/compare