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360
The structure and function of complex networks
 SIAM REVIEW
, 2003
"... Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, ..."
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Cited by 2600 (7 self)
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Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the smallworld effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
A Brief History of Generative Models for Power Law and Lognormal Distributions
 INTERNET MATHEMATICS
"... Recently, I became interested in a current debate over whether file size distributions are best modelled by a power law distribution or a a lognormal distribution. In trying ..."
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Cited by 414 (7 self)
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Recently, I became interested in a current debate over whether file size distributions are best modelled by a power law distribution or a a lognormal distribution. In trying
On Distinguishing between Internet Power Law Topology Generators
, 2002
"... Recent work has shown that the node degree in the WWW induced graph and the ASlevel Internet topology exhibit power laws. Since then several algorithms have been proposed to generate such power law graphs. In this paper we evaluate the effectiveness of these generators to generate representative AS ..."
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Cited by 256 (4 self)
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Recent work has shown that the node degree in the WWW induced graph and the ASlevel Internet topology exhibit power laws. Since then several algorithms have been proposed to generate such power law graphs. In this paper we evaluate the effectiveness of these generators to generate representative ASlevel topologies. Our conclusions are mixed. Although they (mostly) do a reasonable job at capturing the power law exponent, they do less well in capturing the clustering phenomena exhibited by the Internet topology. Based on these results we propose a variation of the recent incremental topology generator of [6] that is more successful at matching the power law exponent and the clustering behavior of the Internet. Last, we comment on the small world behavior of the Internet topology.
The degree sequence of a scalefree random graph process
, 2001
"... Recently, Barabási and Albert [2] suggested modeling complex realworld networks such as the worldwide web as follows: consider a random graph process in which vertices are added to the graph one at a time and joined to a fixed number of earlier vertices, selected with probabilities proportional ..."
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Cited by 243 (2 self)
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Recently, Barabási and Albert [2] suggested modeling complex realworld networks such as the worldwide web as follows: consider a random graph process in which vertices are added to the graph one at a time and joined to a fixed number of earlier vertices, selected with probabilities proportional to their degrees. In [2] and, with Jeong, in [3], Barabási and Albert suggested that after many steps the proportion Pd of vertices with degree d should obey a power law Pdαd−γ. They obtained γ = 29 ± 01 by experiment and gave a simple heuristic argument suggesting that γ = 3. Here we obtain Pd asymptotically for all d ≤ n1/15, where n is the number of vertices, proving as a consequence that γ = 3.
Geographic routing in social networks
, 2005
"... We live in a “small world,” where two arbitrary people are likely connected by a short chain of intermediate friends. With scant information about a target individual, people can successively forward a message along such a chain. Experimental studies have verified this property in real social networ ..."
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Cited by 232 (10 self)
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We live in a “small world,” where two arbitrary people are likely connected by a short chain of intermediate friends. With scant information about a target individual, people can successively forward a message along such a chain. Experimental studies have verified this property in real social networks, and theoretical models have been advanced to explain it. However, existing theoretical models have not been shown to capture behavior in realworld social networks. Here we introduce a richer model relating geography and socialnetwork friendship, in which the probability of befriending a particular person is inversely proportional to the number of closer people. In a large social network, we show that one third of the friendships are independent of geography, and the remainder exhibit the proposed relationship. Further, we prove analytically that short chains can be discovered in every network exhibiting the relationship.
The Small World Inside Large Metabolic Networks
, 2000
"... We analyze the structuture of a large metabolic network, that of the energy and biosynthesis metabolism of Escherichia coli. This network is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyze the structure of net ..."
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Cited by 218 (7 self)
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We analyze the structuture of a large metabolic network, that of the energy and biosynthesis metabolism of Escherichia coli. This network is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyze the structure of networks involving hundreds or thousands of components by simple visual inspection is impossible, and a quantitative framework is needed to analyze them. We propose a graph theoretical description of the E. coli metabolic network, a description that we hope will prove useful for other genetic networks. We find that this network is a small world graph, a type of graph observed in a variety of seemingly unrelated areas, such as friendship networks in sociology, the structure of electrical power grids, and the nervous system of C. elegans. Moreover, its connectivity follows a power law, another unusual but by no means rare statistical distribution. This architecture may serve to minimize trans...
Mathematical results on scalefree random graphs
 Handbook of Graphs and Networks
, 2003
"... Recently there has been much interest in studying largescale realworld networks and attempting to model their properties using random graphs. Although the study of realworld networks as graphs goes back some time, recent activity perhaps started with the paper of Watts and Strogatz [55] about the ..."
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Cited by 147 (3 self)
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Recently there has been much interest in studying largescale realworld networks and attempting to model their properties using random graphs. Although the study of realworld networks as graphs goes back some time, recent activity perhaps started with the paper of Watts and Strogatz [55] about the ‘smallworld
Towards a theory of scalefree graphs: Definition, properties, and implications
 Internet Mathematics
, 2005
"... Abstract. There is a large, popular, and growing literature on “scalefree ” networks with the Internet along with metabolic networks representing perhaps the canonical examples. While this has in many ways reinvigorated graph theory, there is unfortunately no consistent, precise definition of scale ..."
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Cited by 137 (12 self)
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Abstract. There is a large, popular, and growing literature on “scalefree ” networks with the Internet along with metabolic networks representing perhaps the canonical examples. While this has in many ways reinvigorated graph theory, there is unfortunately no consistent, precise definition of scalefree graphs and few rigorous proofs of many of their claimed properties. In fact, it is easily shown that the existing theory has many inherent contradictions and that the most celebrated claims regarding the Internet and biology are verifiably false. In this paper, we introduce a structural metric that allows us to differentiate between all simple, connected graphs having an identical degree sequence, which is of particular interest when that sequence satisfies a power law relationship. We demonstrate that the proposed structural metric yields considerable insight into the claimed properties of SF graphs and provides one possible measure of the extent to which a graph is scalefree. This structural view can be related to previously studied graph properties such as the various notions of selfsimilarity, likelihood, betweenness and assortativity. Our approach clarifies much of the confusion surrounding the sensational qualitative claims in the current literature, and offers a rigorous and quantitative alternative, while suggesting the potential for a rich and interesting theory. This paper is aimed at readers familiar with the basics of Internet technology and comfortable with a theoremproof style of exposition, but who may be unfamiliar with the existing literature on scalefree networks. 1.
Models of the small world
 J. Stat. Phys
, 2000
"... It is believed that almost any pair of people in the world can be connected to one another by a short chain of intermediate acquaintances, of typical length about six. This phenomenon, colloquially referred to as the ``six degrees of separation,' ' has been the subject of considerable rece ..."
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Cited by 132 (1 self)
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It is believed that almost any pair of people in the world can be connected to one another by a short chain of intermediate acquaintances, of typical length about six. This phenomenon, colloquially referred to as the ``six degrees of separation,' ' has been the subject of considerable recent interest within the physics community. This paper provides a short review of the topic. KEY WORDS: social networks. Small world; networks; disordered systems; graph theory;
The Economics of Social Networks.
 In Advances in Economics and Econometrics, Theory and Applications: Ninth World Congress of the Econometric Society.
, 2006
"... Abstract We analyze the problem of optimal monopoly pricing in social networks in order to characterize the influence of the network topology on the pricing rule. It is shown that this influence depends on the type of providers (local versus global monopoly) and of externalities (consumption versus ..."
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Cited by 118 (2 self)
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Abstract We analyze the problem of optimal monopoly pricing in social networks in order to characterize the influence of the network topology on the pricing rule. It is shown that this influence depends on the type of providers (local versus global monopoly) and of externalities (consumption versus price). We identify two situations where the monopolist does not discriminate across nodes in the network (global monopoly with consumption externalities and local monopoly with price externalities) and characterize the relevant centrality index used to discriminate among nodes in the other situations. We also analyze the robustness of the analysis with respect to changes in demand, and the introduction of bargaining between the monopolist and the consumer. JEL Classification Numbers: D85, D43, C69 Keywords: Social Networks, Monopoly Pricing, Network Externalities, Reference Price, Centrality Measures * We dedicate this paper to the memory of Toni CalvóArmengol, a gifted network theorist and a wonderful friend. We thank Coralio Ballester,