Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Centralidade de Intermediação Multicamada× | Centralidade de Proximidade Multicamadas× | |
|---|---|---|
| Área | Análise de redes | Análise de redes |
| Família | Machine learning | Machine learning |
| Ano de origem | 2013–2014 | 2013–2014 |
| Autor original≠ | De Domenico, M.; Kivelä, M.; Arenas, A. et al. | Kivela, M. et al.; De Domenico, M. et al. |
| Tipo≠ | Centrality measure (multilayer extension) | Centrality measure for multilayer networks |
| Fonte seminal≠ | De 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 ↗ |
| Outros nomes | MBC, multilayer geodesic betweenness, tensorial betweenness centrality, interlayer betweenness centrality | multilayer closeness, multi-layer closeness centrality, MLC, interlayer closeness centrality |
| Relacionados | 5 | 5 |
| Resumo≠ | Multilayer 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 closeness centrality extends the classical closeness centrality measure to networks that contain multiple types of relationships or interaction contexts (layers). Rather than treating each layer in isolation, it computes how quickly a node can reach all others by traversing any combination of available layers, revealing nodes that are structurally efficient connectors across the full network system. |
| ScholarGateConjunto de dados ↗ |
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