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| Centralitat de Grau Multicapa× | Centralitat de grau ponderat× | |
|---|---|---|
| Camp | Anàlisi de xarxes | Anàlisi de xarxes |
| Família | Machine learning | Machine learning |
| Any d'origen≠ | 2013–2014 | 2004 |
| Autor original≠ | Kivelä, M.; De Domenico, M. et al. | Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A. |
| Tipus≠ | Centrality measure for multilayer networks | Centrality measure for weighted networks |
| Font seminal≠ | 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. 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 ↗ |
| Àlies | multilayer degree, multiplex degree centrality, overlapping-layer degree centrality, MDC | node strength, strength centrality, weighted node degree, WDC |
| Relacionats | 6 | 6 |
| Resum≠ | 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. |
| ScholarGateConjunt de dades ↗ |
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