Methoden vergleichen

	Multilayer-Grad-Zentralität	Gewichtete Gradzentralität
Fachgebiet	Netzwerkanalyse	Netzwerkanalyse
Familie	Machine learning	Machine learning
Entstehungsjahr	2013–2014	2004
Urheber	Kivelä, M.; De Domenico, M. et al.	Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.
Typ	Centrality measure for multilayer networks	Centrality measure for weighted networks
Wegweisende Quelle	Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.	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.
Aliasnamen	multilayer degree, multiplex degree centrality, overlapping-layer degree centrality, MDC	node strength, strength centrality, weighted node degree, WDC
Verwandt	6	6
Zusammenfassung	Multilayer 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.