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Using a simple model with link removals as well as link additions, we show that an evolving network is scale free with a degree exponent in the range of (2, 4]. We then establish a relation between the network evolution and a set of…

Mathematical Physics · Physics 2007-05-23 Dinghua Shi , Liming Liu , Xiang Zhu , Huijie Zhou , Binbin Wang

For most technical networks, the interplay of dynamics, traffic and topology is assumed crucial to their evolution. In this paper, we propose a traffic-driven evolution model of weighted technological networks. By introducing a general…

Disordered Systems and Neural Networks · Physics 2009-11-11 Wen-Xu Wang , Bo Hu , Gang Yan , Qing Ou , Bing-Hong Wang

We introduce a deterministic model for scale-free networks, whose degree distribution follows a power-law with the exponent $\gamma$. At each time step, each vertex generates its offsprings, whose number is proportional to the degree of…

Statistical Mechanics · Physics 2009-11-07 S. Jung , S. Kim , B. Kahng

For most networks, the connection between two nodes is the result of their mutual affinity and attachment. In this paper, we propose a mutual selection model to characterize the weighted networks. By introducing a general mechanism of…

Statistical Mechanics · Physics 2009-11-11 Wen-Xu Wang , Bu Hu , Tao Zhou , Bing-Hong Wang , Yan-Bo Xie

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

Statistical Mechanics · Physics 2007-05-23 M. Baiesi , S. S. Manna

Inspired by studies on airline networks we propose a general model for weighted networks in which topological growth and weight dynamics are both determined by cost adversarial mechanism. Since transportation networks are designed and…

Physics and Society · Physics 2007-12-10 Yihong Hu , Daoli Zhu , Yang Li , Bing Su , Bingxin Zhu

Duplication graphs are graphs that grow by duplication of existing vertices, and are important models of biological networks, including protein-protein interaction networks and gene regulatory networks. Three models of graph growth are…

Statistical Mechanics · Physics 2009-11-10 Alpan Raval

We review the main tools which allow for the statistical characterization of weighted networks. We then present two case studies, the airline connection network and the scientific collaboration network, which are representative of critical…

Statistical Mechanics · Physics 2009-11-10 Marc Barthelemy , Alain Barrat , Romualdo Pastor-Satorras , Alessandro Vespignani

We propose a method of generating different scale-free networks, which has several input parameters in order to adjust the structure, so that they can serve as a basis for computer simulation of real-world phenomena. The topological…

Social and Information Networks · Computer Science 2014-01-30 Imre Varga , András Németh , Gergely Kocsis

We present a simple mechanism for generating undirected scale-free networks using random walkers, where the network growth is determined by choosing parent vertices by sequential random walks. We show that this mechanism produces scale-free…

Statistical Mechanics · Physics 2007-05-23 Jari Saramaki , Kimmo Kaski

In most networks, the connection between a pair of nodes is the result of their mutual affinity and attachment. In this letter, we will propose a Mutual Attraction Model to characterize weighted evolving networks. By introducing the initial…

Disordered Systems and Neural Networks · Physics 2009-11-11 Wen-Xu Wang , Bo Hu , Bing-Hong Wang , Gang Yan

We study network growth from a fixed set of initially isolated nodes placed at random on the surface of a sphere. The growth mechanism we use adds edges to the network depending on strictly local gain and cost criteria. Only nodes that are…

Statistical Mechanics · Physics 2008-04-11 Valmir C. Barbosa , Raul Donangelo , Sergio R. Souza

We study a recently introduced class of scale-free networks showing a high clustering coefficient and non-trivial connectivity correlations. We find that the connectivity probability distribution strongly depends on the fine details of the…

Statistical Mechanics · Physics 2009-11-07 Alexei Vazquez , Marian Boguna , Yamir Moreno , Romualdo Pastor-Satorras , Alessandro Vespignani

We develop a simple theoretical framework for the evolution of weighted networks that is consistent with a number of stylized features of real-world data. In our framework, the Barabasi-Albert model of network evolution is extended by…

General Finance · Quantitative Finance 2015-05-13 Massimo Riccaboni , Stefano Schiavo

There is increasing evidence that dense networks occur in on-line social networks, recommendation networks and in the brain. In addition to being dense, these networks are often also scale-free, i.e. their degree distributions follow…

Physics and Society · Physics 2018-05-16 Owen T. Courtney , Ginestra Bianconi

We introduce a new mechanism of connectivity evolution in networks to account for the emergence of scale-free behavior. The mechanism works on a fixed set of nodes and promotes growth from a minimally connected initial topology by the…

Statistical Mechanics · Physics 2007-05-23 Valmir C. Barbosa , Raul Donangelo , Sergio R. Souza

We study scale free simple graphs with an exponent of the degree distribution $\gamma$ less than two. Generically one expects such extremely skewed networks -- which occur very frequently in systems of virtually or logically connected units…

Statistical Mechanics · Physics 2007-05-23 Hamed Seyed-allaei , Ginestra Bianconi , Matteo Marsili

We consider a growing network, whose growth algorithm is based on the preferential attachment typical for scale-free constructions, but where the long-range bonds are disadvantaged. Thus, the probability to get connected to a site at…

Statistical Mechanics · Physics 2009-11-07 R. Xulvi-Brunet , I. M. Sokolov

A large computer program is typically divided into many hundreds or even thousands of smaller units, whose logical connections define a network in a natural way. This network reflects the internal structure of the program, and defines the…

Disordered Systems and Neural Networks · Physics 2009-11-10 Alessandro P. S. de Moura , Ying-Cheng Lai , Adilson E. Motter

The configuration model is one of the most successful models for generating uncorrelated random networks. We analyze its behavior when the expected degree sequence follows a power law with exponent smaller than two. In this situation, the…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. A. Serrano , M. Boguna