Scale-Free Networks from Varying Vertex Intrinsic Fitness

Caldarelli, Guido; Capocci, Andrea; Rios, Paolo De Los; Muñoz, Miguel A.

doi:10.1103/physrevlett.89.258702

Cited by 722 publications

(882 citation statements)

References 23 publications

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“…[1,28,2]. The investigation that is presented later in the text relies on results that are reviewed in the following.…”

Section: The Static Fitness Modelmentioning

confidence: 99%

“…The grossdomestic-product (GDP) was obtained from UN-data 1 . The countries that are covered in the present report are displayed in Tab.…”

Section: The Choice Of a Data Sourcementioning

confidence: 99%

“…However, it is not clear how to define fitness. There is general agreement that fitness is defined over some constraint interval, usually [0,1]. Two different definitions of fitness are investigated in the following.…”

Section: Definition Of Fitnessmentioning

confidence: 99%

“…A detailed understanding of the network structure of international trade facilitates a better comprehension of crises that spread across a country's frontiers. It is generally agreed that a static hidden variable model [1,2] best describes the topology of the WTN. The static model is most suitable because there are only a finite number of distinct countries in the world.…”

Section: Introductionmentioning

confidence: 99%

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A microscopic study of the fitness-dependent topology of the world trade network

Hoppe

Rodgers

2015

Physica A: Statistical Mechanics and its Applications

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Previous studies have suggested that the world-trade network belongs to the class of static hidden variable models. In this article we investigate the microscopic structure of the world trade network, that is the hidden variable correlation matrix of the network. The hidden variable is defined as a rank ordering of gross domestic products. This choice significantly reduces the noise in the statistical analysis found in previous studies. The hidden variable correlation matrix, that expresses the probability that a trade relationship between two countries of given fitness exists, suggests an attachment kernel that at least partially favours trading pairs or dissimilar fitness rather than the purely multiplicative one found previously. Additionally, we provide an in-depth look at the data source and reveal that first-order results, such as the degree distribution, exhibit significant qualitative differences depending on the data provider. Furthermore, we shed light on the intertemporal activity of international trade and point out that fluctuations occur mostly between countries with strong dissimilarities of fitness and connectivity.

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“…[1,28,2]. The investigation that is presented later in the text relies on results that are reviewed in the following.…”

Section: The Static Fitness Modelmentioning

confidence: 99%

“…The grossdomestic-product (GDP) was obtained from UN-data 1 . The countries that are covered in the present report are displayed in Tab.…”

Section: The Choice Of a Data Sourcementioning

confidence: 99%

Section: Definition Of Fitnessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A microscopic study of the fitness-dependent topology of the world trade network

Hoppe

Rodgers

2015

Physica A: Statistical Mechanics and its Applications

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“…It is worthwhile to argue the degree distribution function of a non-evolving network with a local-world property. The fitness model proposed by Caldarelli et al [15] is known to be a representative non-evolving scale-free network model. We can incorporate the local-world nature into the fitness model by restricting a node to connect other nodes only in a randomly chosen local-world subset of size M .…”

Section: Crossover Behavior Of the Local-world Evolving Networkmentioning

confidence: 99%

Scale-free property of local-world networks and their community structures

Furuya¹,

Yakubo²

2010

Physica A: Statistical Mechanics and its Applications

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The scale-free property and community structures of complex networks formed by local events have been studied theoretically, numerically, and empirically. We showed analytically and numerically that the degree distribution function P (k) of the local-world evolving network exhibits a crossover from an exponential to power-law form by increasing the local-world size M . For M much larger than the crossover local-world size M co , the distribution function P (k) has a power-law form for any degree k(≫ 1). Below M co , however, P (k) obeys a power law for 1 ≪ k ≪ k co and decays exponentially for k ≫ k co . The crossover size M co and the crossover degree k co have been also elucidated. In addition, we constructed the drug prescription network (DPN) as a real local-world network, in which the local-world subsets are definitely specified, to reveal how the local-world nature affects properties of real-world networks. We found that the community structure of the DPN strongly correlates with the local worlds.

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2011

Data Management of Protein Interaction Networks

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Scale-Free Networks from Varying Vertex Intrinsic Fitness

Cited by 722 publications

References 23 publications

A microscopic study of the fitness-dependent topology of the world trade network

A microscopic study of the fitness-dependent topology of the world trade network

Scale-free property of local-world networks and their community structures

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