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Identification of influential spreaders in complex networks
M. Kitsak, L. Gallos, S. Havlin, F. Liljeros, L. Muchnik, H. Stanley, and H. Makse, "Identification of influential spreaders in complex networks", Nature Physics, vol. 6, no. 11, pp. 888--893, Aug 2010.
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Identification of influential spreaders in complex networks

Maksim Kitsak1, 2, 8
Lazaros Gallos6, 10
Shlomo Havlin3, 7
Fredrik Liljeros4
Lev Muchnik5
H. Eugene Stanley2, 8
Hernán Makse6, 9

CAIDA, San Diego Supercomputer Center, University of California San Diego


Center for Polymer Studies, Boston University


Department of Physics, Bar-Ilan University


Department of Sociology, Stockholm University


Information Operations and Management Sciences
Stern School of Business


Levich Institute


Minerva Center


Physics Department, Boston University


Physics Department, City College of New York


Physics Department, University of Thessaloniki

Networks portray a multitude of interactions through which people meet, ideas are spread, and infectious diseases propagate within a society. Identifying the most efficient "spreaders" in a network is an important step to optimize the use of available resources and ensure the more efficient spread of information. Here we show that, in contrast to common belief, the most influential spreaders in a social network do not correspond to the best connected people or to the most central people (high betweenness centrality). Instead, we find: (i) The most efficient spreaders are those located within the core of the network as identified by the k-shell decomposition analysis. (ii) When multiple spreaders are considered simultaneously, the distance between them becomes the crucial parameter that determines the extend of the spreading. Furthermore, we find that-- in the case of infections that do not confer immunity on recovered individuals-- the infection persists in the high k-shell layers of the network under conditions where hubs may not be able to preserve the infection. Our analysis provides a plausible route for an optimal design of efficient dissemination strategies.

Keywords: routing, topology
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