Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis de Redes de Mundo Pequeño y Libres de Escala× | Análisis de Resiliencia y Vulnerabilidad de Redes× | |
|---|---|---|
| Campo | Análisis de redes | Análisis de redes |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1998 (small-world); 1999 (scale-free) | 2000 |
| Autor original≠ | — | Albert, Jeong & Barabási |
| Tipo≠ | Descriptive / exploratory network analysis | Network robustness / vulnerability framework |
| Fuente seminal≠ | Watts, D.J. & Strogatz, S.H. (1998). Collective Dynamics of 'Small-World' Networks. Nature, 393(6684), 440-442. DOI ↗ | Albert, R., Jeong, H. & Barabási, A.L. (2000). Error and attack tolerance of complex networks. Nature, 406, 378–382. DOI ↗ |
| Alias≠ | Küçük Dünya ve Ölçek-Bağımsız Ağ Analizi, small-world network, scale-free network, preferential attachment analysis | network vulnerability analysis, attack tolerance analysis, Ağ Dayanıklılığı ve Güvenlik Açığı Analizi |
| Relacionados≠ | 9 | 5 |
| Resumen≠ | Small-world and scale-free network analysis tests whether a real-world network exhibits two landmark topological signatures identified in 1998-1999: the Watts-Strogatz small-world property (high local clustering combined with short average path lengths) and the Barabási-Albert scale-free property (a degree distribution that follows a power law, meaning a small number of hubs connect to a disproportionately large share of other nodes). Together these frameworks transformed network science by showing that many social, biological, and technological networks share a common structural grammar. | Network resilience and vulnerability analysis is an analytical framework, formalised by Albert, Jeong, and Barabási (2000), that measures how a network degrades functionally as nodes or edges are progressively removed. By running targeted-attack simulations — removing the highest-centrality nodes first — and random-failure simulations — removing nodes at uniform probability — the framework identifies which structural elements are critical to network integrity and where infrastructure is most exposed. |
| ScholarGateConjunto de datos ↗ |
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