Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Vērsta divu režīmu tīkla analīze× | Daudzslāņu tīklu analīze× | |
|---|---|---|
| Nozare | Tīklu analīze | Tīklu analīze |
| Saime | Machine learning | Machine learning |
| Izcelsmes gads≠ | 1997 | 2014 |
| Autors≠ | Borgatti, S. P. & Everett, M. G. | Kivela, M.; Boccaletti, S. et al. |
| Tips≠ | Structural network analysis | Structural network model |
| Pirmavots≠ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications (Ch. 8). Cambridge University Press. ISBN: 978-0-521-38707-1 | 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 ↗ |
| Citi nosaukumi | directed bipartite network analysis, asymmetric affiliation network analysis, directed actor-event network analysis, directed two-mode graph analysis | multiplex networks, multi-layer network analysis, multilayer network analysis, MNA |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Directed two-mode network analysis studies bipartite graphs in which nodes belong to two distinct sets — such as actors and events, authors and papers, or firms and markets — and edges carry a direction, capturing asymmetric relationships like citation, referral, or endorsement. Combining the duality of two-mode structure with directed tie semantics reveals flow patterns and influence asymmetries that undirected or single-mode analyses would miss. | Multiplex network analysis studies systems where the same set of nodes is connected by multiple distinct types of relationships, each represented as a separate network layer. By analyzing layers simultaneously rather than in isolation, it reveals how different relation types interact, reinforce each other, or compensate for one another across the same actors or entities. |
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