Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Svērta divu veidu tīklu analīze× | Divu-modālā tīklu analīze× | |
|---|---|---|
| Nozare | Tīklu analīze | Tīklu analīze |
| Saime | Machine learning | Machine learning |
| Izcelsmes gads≠ | 1997 (two-mode); weighted extensions 2000s | 1974 |
| Autors≠ | Borgatti, S. P. & Everett, M. G. | Breiger, R. L. |
| Tips≠ | Network structural analysis | Bipartite graph analysis |
| Pirmavots≠ | Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269. DOI ↗ | Breiger, R. L. (1974). The duality of persons and groups. Social Forces, 53(2), 181–190. DOI ↗ |
| Citi nosaukumi | weighted bipartite network analysis, valued two-mode network analysis, weighted affiliation network analysis, W2MNA | bipartite network analysis, affiliation network analysis, two-mode SNA, dual-projection network analysis |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Weighted two-mode network analysis examines bipartite graphs in which two distinct node sets — such as actors and events, authors and papers, or species and habitats — are connected by edges carrying numerical weights that capture the strength, frequency, or intensity of each affiliation. Incorporating weights provides substantially richer structural insights than unweighted bipartite analysis. | Two-mode network analysis examines networks built from two distinct types of nodes — such as actors and events, authors and papers, or companies and board members — connected only across types. By analysing this bipartite structure directly or projecting it onto one-mode networks, researchers uncover affiliation patterns, shared memberships, and structural duality that are invisible in standard one-mode social network analysis. |
| ScholarGateDatu kopa ↗ |
|
|