Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de la diffusion en réseau× | Analyse des réseaux sociaux× | |
|---|---|---|
| Domaine | Analyse de réseaux | Analyse de réseaux |
| Famille | Machine learning | Machine learning |
| Année d'origine≠ | 1927 (epidemic roots); network formalization 1990s–2000s | 1934 (sociometry); 1994 (modern formalization) |
| Auteur d'origine≠ | Kermack, W. O. & McKendrick, A. G. | Moreno, J.L.; formalized by Wasserman & Faust |
| Type≠ | Simulation / analytical model | Structural/relational analysis framework |
| Source fondatrice≠ | Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Alias | diffusion on networks, information diffusion, contagion spreading model, network propagation model | SNA, network analysis, sociometric analysis, relational analysis |
| Apparentées | 5 | 5 |
| Résumé≠ | Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally. | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. |
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