Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Vážená blízkostní centralita× | Analýza vážených sociálních sítí× | |
|---|---|---|
| Obor | Analýza sítí | Analýza sítí |
| Rodina | Machine learning | Machine learning |
| Rok vzniku≠ | 2010 | 2004–2010 |
| Tvůrce≠ | Opsahl, T.; Agneessens, F.; Skvoretz, J. | Barrat, A.; Opsahl, T. et al. |
| Typ≠ | Centrality measure (network analysis) | Network analysis framework |
| Původní zdroj≠ | Opsahl, T., Agneessens, F. & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251. 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 ↗ |
| Další názvy | weighted closeness, generalized closeness centrality, WCC, distance-weighted closeness | Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis |
| Příbuzné | 6 | 6 |
| Shrnutí≠ | Weighted closeness centrality extends the classic closeness measure to networks where edges carry numerical weights — such as frequency, strength, or cost — by incorporating those weights into shortest-path distances. Nodes that can reach others quickly along strong or efficient connections receive higher scores, making it a richer indicator of information-spreading potential than its binary counterpart. | 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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