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Analiza mrežne difuzije×Centralnost svojstvenog vektora×
PodručjeAnaliza mrežaAnaliza mreža
ObiteljMachine learningMachine learning
Godina nastanka1927 (epidemic roots); network formalization 1990s–2000s1972
TvoracKermack, W. O. & McKendrick, A. G.Bonacich, P.
VrstaSimulation / analytical modelCentrality measure
Temeljni izvorKermack, 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 ↗Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120. DOI ↗
Drugi nazividiffusion on networks, information diffusion, contagion spreading model, network propagation modeleigenvector centrality, EC, Bonacich centrality, power centrality
Srodne56
SažetakNetwork 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.Eigenvector centrality, introduced by Bonacich in 1972, measures a node's influence by considering not just how many neighbors it has, but how influential those neighbors are. A node scores highly if it is connected to other high-scoring nodes, making it a recursive, globally-aware measure of structural importance in a network.
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ScholarGateUsporedite metode: Network Diffusion Analysis · Eigenvector Centrality. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare