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계열Machine learningMachine learning
기원 연도20141927 (epidemic roots); network formalization 1990s–2000s
창시자Kivela, M.; Boccaletti, S. et al.Kermack, W. O. & McKendrick, A. G.
유형Structural network modelSimulation / analytical model
원전Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗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 ↗
별칭multiplex networks, multi-layer network analysis, multilayer network analysis, MNAdiffusion on networks, information diffusion, contagion spreading model, network propagation model
관련65
요약Multiplex network analysis studies systems where the same set of nodes is connected by multiple distinct types of relationships, each represented as a separate network layer. By analyzing layers simultaneously rather than in isolation, it reveals how different relation types interact, reinforce each other, or compensate for one another across the same actors or entities.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.
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