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We study the growth of a directed network, in which the growth is constrained by the cost of adding links to the existing nodes. We propose a new preferential-attachment scheme, in which a new node attaches to an existing node i with…

统计力学 · 物理学 2007-05-23 Volkan Sevim , Per Arne Rikvold

Small-world networks are the focus of recent interest because they appear to circumvent many of the limitations of either random networks or regular lattices as frameworks for the study of interaction networks of complex systems. Here, we…

统计力学 · 物理学 2012-03-08 Luis A. Nunes Amaral , Antonio Scala , Marc Barthelemy , H. Eugene Stanley

We propose and study a model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent. The model represents a hybrid of the growing networks based on…

无序系统与神经网络 · 物理学 2009-11-10 H. Y. Lee , H. Y. Chan , P. M. Hui

We introduce a network evolution process motivated by the network of citations in the scientific literature. In each iteration of the process a node is born and directed links are created from the new node to a set of target nodes already…

物理与社会 · 物理学 2013-07-30 ER Colman , GJ Rodgers

In this article, we propose a growing network model based on an optimal policy involving both topological and geographical measures. In this model, at each time step, a new node, having randomly assigned coordinates in a $1 \times 1$…

物理与社会 · 物理学 2007-05-23 Yan-Bo Xie , Tao Zhou , Wen-Jie Bai , Guanrong Chen , Wei-Ke Xiao , Bing-Hong Wang

We study the organization and dynamics of growing directed networks. These networks are built by adding nodes successively in such a way that each new node has $K$ directed links to the existing ones. The organization of a growing directed…

统计力学 · 物理学 2016-08-31 Baosheng Yuan , Kan Chen , Bing-Hong Wang

In this paper, we propose an evolving network model growing fast in units of module, based on the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected…

物理与社会 · 物理学 2011-10-11 Zou Zhi-Yun , Liu Peng , Lei Li , Gao Jian-Zhi

Many real networks are complex and have power-law vertex degree distribution, short diameter, and high clustering. We analyze the network model based on thresholding of the summed vertex weights, which belongs to the class of networks…

其他凝聚态物理 · 物理学 2007-05-23 Naoki Masuda , Hiroyoshi Miwa , Norio Konno

Undirected hyperbolic graph models have been extensively used as models of scale-free small-world networks with high clustering coefficient. Here we presented a simple directed hyperbolic model, where nodes randomly distributed on a…

物理与社会 · 物理学 2023-11-28 I. A. Kasyanov , P. van der Hoorn , D. Krioukov , M. V. Tamm

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…

统计力学 · 物理学 2009-11-07 S. Jung , S. Kim , B. Kahng

Several fundamental properties of real complex networks, such as the small-world effect, the scale-free degree distribution, and recently discovered topological fractal structure, have presented the possibility of a unique growth mechanism…

数据分析、统计与概率 · 物理学 2009-11-13 Liuhua Zou , Wenjiang Pei , Tao Li , Zhenya He , Yiuming Cheung

Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information…

无序系统与神经网络 · 物理学 2016-08-31 Albert-Laszlo Barabasi , Reka Albert , Hawoong Jeong

We proposed a deterministic multidimensional growth model for small-world networks. The model can characterize the distinguishing properties of many real-life networks with geometric space structure. Our results show the model possesses…

数据分析、统计与概率 · 物理学 2017-12-27 Aoyuan Peng , Lianming Zhang

The degree distributions of many real world networks follow power-laws whose exponents tend to fall between two and three. Within the framework of the Barabasi-Albert model (BA model), we explain this empirical observation by a simple fact.…

物理与社会 · 物理学 2009-05-19 Shinji Tanimoto

We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which are partially determined by the parameters. Analytical…

物理与社会 · 物理学 2011-11-09 Zhongzhi Zhang , Shuigeng Zhou , Lichao Chen , Jihong Guan , Lujun Fang , Yichao Zhang

While the emergence of a power law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the betweenness centrality displays a power-law distribution with an exponent \eta which is…

统计力学 · 物理学 2009-11-07 K. -I. Goh , E. OH , H. Jeong , B. Kahng , D. Kim

We propose a natural model of evolving weighted networks in which new links are not necessarily connected to new nodes. The model allows a newly added link to connect directly two nodes already present in the network. This is plausible in…

物理与社会 · 物理学 2011-08-18 Shinji Tanimoto

We extend the merging model for undirected networks by Kim et al. [Eur. Phys. J. B 43, 369 (2004)] to directed networks and investigate the emerging scale-free networks. Two versions of the directed merging model, friendly and hostile…

统计力学 · 物理学 2007-05-23 Sebastian Bernhardsson , Petter Minnhagen

We introduce a general deterministic model for Apollonian Networks in an iterative fashion. The networks have small-world effect and scale-free topology. We calculate the exact results for the degree exponent, the clustering coefficient and…

统计力学 · 物理学 2007-05-23 Zhongzhi Zhang , Lili Rong

A degree-corrected distribution-free model is proposed for weighted social networks with latent structural information. The model extends the previous distribution-free models by considering variation in node degree to fit real-world…

社会与信息网络 · 计算机科学 2024-04-08 Huan Qing