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| Phân tích khuếch tán mạng có trọng số× | Phân tích Mạng Xã hội Có trọng số× | |
|---|---|---|
| Lĩnh vực | Phân tích mạng lưới | Phân tích mạng lưới |
| Họ | Machine learning | Machine learning |
| Năm ra đời≠ | 2004 | 2004–2010 |
| Người khởi xướng≠ | Barrat, A.; Newman, M. E. J. | Barrat, A.; Opsahl, T. et al. |
| Loại≠ | Network diffusion model | Network analysis framework |
| Công trình gốc≠ | 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 ↗ |
| Tên gọi khác | WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion | Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | 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. |
| ScholarGateBộ dữ liệu ↗ |
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