Comparer des méthodes

	Analyse de la diffusion en réseau	Centralité d'intermédiarité
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	1927 (epidemic roots); network formalization 1990s–2000s	1977
Auteur d'origine	Kermack, W. O. & McKendrick, A. G.	Freeman, L. C.
Type	Simulation / analytical model	Centrality measure
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.	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.
Alias	diffusion on networks, information diffusion, contagion spreading model, network propagation model	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness
Apparentées	5	6
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.	Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes.