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تحليل الانتشار الشبكي×مركزية المتجه الذاتي×
المجالتحليل الشبكاتتحليل الشبكات
العائلةMachine learningMachine learning
سنة النشأة1927 (epidemic roots); network formalization 1990s–2000s1972
صاحب الطريقةKermack, W. O. & McKendrick, A. G.Bonacich, P.
النوعSimulation / analytical modelCentrality measure
المصدر التأسيسيKermack, 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 ↗
الأسماء البديلةdiffusion on networks, information diffusion, contagion spreading model, network propagation modeleigenvector centrality, EC, Bonacich centrality, power centrality
ذات صلة56
الملخصNetwork 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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ScholarGateقارن الطرق: Network Diffusion Analysis · Eigenvector Centrality. استُرجع بتاريخ 2026-06-15 من https://scholargate.app/ar/compare