Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ направленных мультиплексных сетей× | Анализ направленных социальных сетей× | |
|---|---|---|
| Область | Сетевой анализ | Сетевой анализ |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 2013–2014 | 1994 |
| Автор метода≠ | Kivela, M.; De Domenico, M. et al. | Wasserman, S. & Faust, K. |
| Тип≠ | Multi-layer directed graph framework | Structural analysis of directed graphs |
| Основополагающий источник≠ | 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 ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Другие названия | directed multilayer network analysis, directed multiplex graphs, asymmetric multiplex network analysis, DMNA | directed SNA, digraph analysis, directed graph network analysis, asymmetric network analysis |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Directed multiplex network analysis models systems where the same set of nodes are connected by multiple types of directed (asymmetric) relationships across distinct layers — such as citation flows, information cascades, or authority hierarchies co-existing simultaneously. It extends multiplex network analysis by preserving both layer identity and edge directionality, enabling richer structural and dynamic insights. | Directed Social Network Analysis (directed SNA) studies networks in which every tie has an explicit direction — from a sender to a receiver — rather than treating relationships as symmetric. It extends the classical SNA toolkit with in-degree, out-degree, reciprocity, and asymmetric path measures, making it the appropriate framework wherever relationship direction carries substantive meaning, such as citation flows, advice-seeking, follower graphs, or information cascades. |
| ScholarGateНабор данных ↗ |
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