2008
DOI: 10.1103/revmodphys.80.1275
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Critical phenomena in complex networks

Abstract: The combination of the compactness of networks, featuring small diameters, and their complex architectures results in a variety of critical effects dramatically different from those in cooperative systems on lattices. In the last few years, researchers have made important steps toward understanding the qualitatively new critical phenomena in complex networks. We review the results, concepts, and methods of this rapidly developing field. Here we mostly consider two closely related classes of these critical phen… Show more

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Cited by 2,021 publications
(2,235 citation statements)
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References 407 publications
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“…In a large random network node degrees are distributed according to the normal distribution, but in many manmade and biological networks the degree distribution follows a power-law. In the human protein-protein interaction networks 3,4 , for instance, some proteins act as hubs, they are highly connected, and interact with more than 200 other proteins contrary to most proteins that interact with only a few other proteins.Various local to global measures have been introduced to unveil the organizational principles of complex networks 5,6,7,8,9 . Maslov and Sneppen 10 discovered that who links to whom can depend on node degree; in many biological networks, high degree nodes systematically link to nodes of low degree.…”
mentioning
confidence: 99%
“…In a large random network node degrees are distributed according to the normal distribution, but in many manmade and biological networks the degree distribution follows a power-law. In the human protein-protein interaction networks 3,4 , for instance, some proteins act as hubs, they are highly connected, and interact with more than 200 other proteins contrary to most proteins that interact with only a few other proteins.Various local to global measures have been introduced to unveil the organizational principles of complex networks 5,6,7,8,9 . Maslov and Sneppen 10 discovered that who links to whom can depend on node degree; in many biological networks, high degree nodes systematically link to nodes of low degree.…”
mentioning
confidence: 99%
“…Our analysis also applies to models for rotators σ ∈ S q taking values in the q-dimensional sphere with the O(q)-invariant interaction e Φ(σ,σ ′ ) = c + θ σ, σ ′ , see Section 5.3. They are believed to be in the same universality class as the ones with the standard interaction e Φ(σ,σ ′ ) = e θ σ,σ ′ [15]. This is a statement whose full mathematical justification would however need an investigation of the corresponding infinite-dimensional fixed point problem, and would be an interesting analytical problem in itself for future study.…”
Section: Introductionmentioning
confidence: 99%
“…describe an opinion or an internal state of a person [33] or neurons in the brain [19]. The interaction between the behavior of spin models and the properties of the random graph is of special interest, see for example [15] for an overview of (often non-rigorous) results in the physics literature.…”
Section: Introductionmentioning
confidence: 99%
“…It is conducive to containing epidemic spread, studying information dissemination, and controlling virus diffusion [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. In this view, researchers have developed various methods, such as degree centrality (DC) [15], betweenness centrality (BC) [16], closeness centrality (CC) [17], and semilocal centrality [18] to identify the most influential spreaders in a network.…”
Section: Introductionmentioning
confidence: 99%