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In the consensus model with bounded confidence, studied by Deffuant et al. (2000), two randomly selected people who differ not too much in their opinion both shift their opinions towards each other. Now we restrict this exchange of…

Statistical Mechanics · Physics 2009-11-10 D. Stauffer , H. Meyer-Ortmanns

Real-life networks often encounter vertex dysfunctions, which are usually followed by recoveries after appropriate maintenances. In this paper we present our research on a model of scale-free networks whose vertices are regularly removed…

Physics and Society · Physics 2013-10-08 Linjun Li , Xiangwen Wang

We give exact relations for certain types of the hierarchic fractal structures. In the blatant distinction from regular networks of the "small world" (SW) topology [1], regular fractal networks manifests the logarithmic dependence of the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Gregory Surdutovich , Vladimir Gol'dshtein , Gennady Koganov

We review the recent fast progress in statistical physics of evolving networks. Interest has focused mainly on the structural properties of random complex networks in communications, biology, social sciences and economics. A number of giant…

Statistical Mechanics · Physics 2015-06-24 S. N. Dorogovtsev , J. F. F. Mendes

We analyze about two hundred naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned…

We found that models of evolving random networks exhibit dynamic scaling similar to scaling of growing surfaces. It is demonstrated by numerical simulations of two variants of the model in which nodes are added as well as removed [Phys.…

Statistical Mechanics · Physics 2009-11-07 Miroslav Kotrla , Frantisek Slanina , Jakub Steiner

We provide a simple proof that graphs in a general class of self-similar networks have zero percolation threshold. The considered self-similar networks include random scale-free graphs with given expected node degrees and zero clustering,…

Disordered Systems and Neural Networks · Physics 2011-01-28 M. Angeles Serrano , Dmitri Krioukov , Marian Boguna

This research establishes that many real-world networks exhibit bounded expansion, a strong notion of structural sparsity, and demonstrates that it can be leveraged to design efficient algorithms for network analysis. We analyze several…

Social and Information Networks · Computer Science 2018-10-15 Erik D. Demaine , Felix Reidl , Peter Rossmanith , Fernando Sanchez Villaamil , Somnath Sikdar , Blair D. Sullivan

We generalize the scale-free network model of Barab\`asi and Albert [Science 286, 509 (1999)] by proposing a class of stochastic models for scale-free interdependent networks in which interdependent nodes are not randomly connected but…

Physics and Society · Physics 2015-06-11 Boris Podobnik , Davor Horvatic , Mark Dickison , H. Eugene Stanley

We give an intuitive though general explanation of the finite-size effect in scale-free networks in terms of the degree distribution of the starting network. This result clarifies the relevance of the starting network in the final degree…

Physics and Society · Physics 2011-07-14 Sara Cuenda , Juan A. Crespo

Most real complex networks -- such as protein interactions, social contacts, the internet -- are only partially known and available to us. While the process of exploring such networks in many cases resembles a random walk, it becomes a key…

Physics and Society · Physics 2007-09-19 Luciano da Fontoura Costa

A network is formed using the $N$ sites of an one-dimensional lattice in the shape of a ring as nodes and each node with the initial degree $k_{in}=2$. $N$ links are then introduced to this network, each link starts from a distinct node,…

Statistical Mechanics · Physics 2009-11-07 G. Mukherjee , S. S. Manna

With the evolution of social networks, the network structure shows dynamic nature in which nodes and edges appear as well as disappear for various reasons. The role of a node in the network is presented as the number of interactions it has…

Social and Information Networks · Computer Science 2018-03-02 Shailesh Kumar Jaiswal , Nabajyoti Medhi , Manjish Pal , Mridul Sahu , Prashant Sahu , Amal Dev Sarma

Based on the concept and techniques of first-passage probability in Markov chain theory, this letter provides a rigorous proof for the existence of the steady-state degree distribution of the scale-free network generated by the…

Probability · Mathematics 2008-05-13 Zhenting Hou , Xiangxing Kong , Dinghua Shi , Guanrong Chen

In this paper, firstly, we study analytically the topological features of a family of hierarchical lattices (HLs) from the view point of complex networks. We derive some basic properties of HLs controlled by a parameter $q$. Our results…

Statistical Mechanics · Physics 2007-05-23 Zhongzhi Zhang , Shuigeng Zhou , Tao Zou

One of the main characteristics of real-world networks is their large clustering. Clustering is one aspect of a more general but much less studied structural organization of networks, i.e. edge multiplicity, defined as the number of…

Physics and Society · Physics 2012-01-31 Vinko Zlatic , Diego Garlaschelli , Guido Caldarelli

We investigate the influence of the network's size on the degree distribution in Barabasi-Albert model of growing network with initial attractiveness. Our approach based on spectral moments allows to treat analytically several variants of…

Statistical Mechanics · Physics 2007-06-13 B. Waclaw , I. M. Sokolov

In complex systems, responses to small perturbations are too diverse to predict how much they would be definitely, and then such diverse responses can be predicted in a probabilistic way. Here we study such a problem in scale-free networks,…

Statistical Mechanics · Physics 2007-05-23 J. -H. Kim , K. -I. Goh , B. Kahng , D. Kim

We study Erd\"{o}s-R\'enyi random graphs with random weights associated with each link. We generate a new ``Supernode network'' by merging all nodes connected by links having weights below the percolation threshold (percolation clusters)…

Disordered Systems and Neural Networks · Physics 2015-06-25 Tomer Kalisky , Sameet Sreenivasan , Lidia A. Braunstein , Sergey V. Buldyrev , Shlomo Havlin , H. Eugene Stanley

With a simple attack and repair evolution model, we investigate and compare the stability of the Erdos-Renyi random graphs (RG) and Barabasi-Albert scale-free (SF) networks. We introduce a new quantity, invulnerability I(s), to describe the…

Statistical Mechanics · Physics 2009-11-11 L. P. Chi , C. B. Yang , X. Cai
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