Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Svērtas tīklu difūzijas analīze× | Svērta sociālā tīkla analīze× | |
|---|---|---|
| Nozare | Tīklu analīze | Tīklu analīze |
| Saime | Machine learning | Machine learning |
| Izcelsmes gads≠ | 2004 | 2004–2010 |
| Autors≠ | Barrat, A.; Newman, M. E. J. | Barrat, A.; Opsahl, T. et al. |
| Tips≠ | Network diffusion model | Network analysis framework |
| Pirmavots≠ | Barrat, A., Barthelemy, 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 ↗ | 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 ↗ |
| Citi nosaukumi | WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion | Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Weighted Network Diffusion Analysis models how information, influence, disease, or resources spread through a network whose edges carry quantitative strength values. By letting tie weights govern transition probabilities, the method produces more realistic spreading dynamics than binary-edge diffusion, revealing which high-traffic pathways dominate propagation in social, biological, and information networks. | Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the existence, of their relationships. |
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