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相关论文: Generalized Network Growth: from Microscopic Strat…

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In this paper we present a new version of a network growth model, generalized in order to describe the behavior of social networks. The case of study considered is the preprint archive at cul.arxiv.org. Each node corresponds to a scientist,…

凝聚态物理 · 物理学 2009-11-10 Michele Catanzaro , Guido Caldarelli , Luciano Pietronero

Real networks often grow through the sequential addition of new nodes that connect to older ones in the graph. However, many real systems evolve through the branching of fundamental units, whether those be scientific fields, countries, or…

物理与社会 · 物理学 2020-06-30 Muhua Zheng , Guillermo García-Pérez , Marián Boguñá , M. Ángeles Serrano

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement…

统计力学 · 物理学 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

We introduce a growing network model in which a new node attaches to a randomly-selected node, as well as to all ancestors of the target node. This mechanism produces a sparse, ultra-small network where the average node degree grows…

统计力学 · 物理学 2009-11-10 P. L. Krapivsky , S. Redner

We propose a general geometric growth model for pseudofractal scale-free web, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks: degree distribution, second moment of degree…

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

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

Structure and dynamics of complex networks usually deal with degree distributions, clustering, shortest path lengths and other graph properties. Although these concepts have been analysed for graphs on abstract spaces, many networks happen…

统计力学 · 物理学 2009-11-13 M. O. Hase , J. F. F. Mendes

We study a class of growth algorithms for directed graphs that are candidate models for the evolution of genetic regulatory networks. The algorithms involve partial duplication of nodes and their links, together with innovation of new…

分子网络 · 定量生物学 2007-05-23 D. V. Foster , S. A. Kauffman , J. E. S. Socolar

We propose a model for growing networks based on a finite memory of the nodes. The model shows stylized features of real-world networks: power law distribution of degree, linear preferential attachment of new links and a negative…

凝聚态物理 · 物理学 2009-11-07 Konstantin Klemm , Victor M. Eguiluz

The Internet topology at the Autonomous Systems level (AS graph) has a power--law degree distribution and a tier structure. In this paper, we introduce the Interactive Growth (IG) model based on the joint growth of new nodes and new links.…

网络与互联网体系结构 · 计算机科学 2008-12-15 Shi Zhou , Raul J. Mondragon

We introduce a minimal model of small-world growing network generated by attaching to edges. The produced network is a plane graph which exists in real-life world. We obtain the analytic results of degree distribution decaying exponentially…

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

The analysis in this paper helps to explain the formation of growing networks with degree distributions that follow extended exponential or power-law tails. We present a generic model in which edge dynamics are driven by a continuous…

物理与社会 · 物理学 2020-11-12 Jan Medina-López , Jorge Finke

In this paper we introduce a model of spatial network growth in which nodes are placed at randomly selected locations on a unit square in $\mathbb{R}^2$, forming new connections to old nodes subject to the constraint that edges do not…

物理与社会 · 物理学 2016-02-12 Garvin Haslett , Seth Bullock , Markus Brede

This paper proposes an attributed network growth model. Despite the knowledge that individuals use limited resources to form connections to similar others, we lack an understanding of how local and resource-constrained mechanisms explain…

社会与信息网络 · 计算机科学 2019-04-17 Harshay Shah , Suhansanu Kumar , Hari Sundaram

Our work introduces an approach for estimating the contribution of attachment mechanisms to the formation of growing networks. We present a generic model in which growth is driven by the continuous attachment of new nodes according to…

概率论 · 数学 2019-02-20 Jan Medina , Jorge Finke , Camilo Rocha

In the context of growing networks, we introduce a simple dynamical model that unifies the generic features of real networks: scale-free distribution of degree and the small world effect. While the average shortest path length increases…

凝聚态物理 · 物理学 2009-11-07 Konstantin Klemm , Victor M. Eguiluz

Real growing networks like the WWW or personal connection based networks are characterized by a high degree of clustering, in addition to the small-world property and the absence of a characteristic scale. Appropriate modifications of the…

统计力学 · 物理学 2009-11-07 Gabor Szabo , Mikko Alava , Janos Kertesz

We analyze a model of interacting agents (e.g. prebiotic chemical species) which are represended by nodes of a network, whereas their interactions are mapped onto directed links between these nodes. On a fast time scale, each agent follows…

种群与进化 · 定量生物学 2009-11-13 Adrian M. Seufert , Frank Schweitzer

Many real systems possess accelerating statistics where the total number of edges grows faster than the network size. In this paper, we propose a simple weighted network model with accelerating growth. We derive analytical expressions for…

物理与社会 · 物理学 2008-11-20 Zhongzhi Zhang , Lujun Fang , Shuigeng Zhou , Jihong Guan

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…

无序系统与神经网络 · 物理学 2009-11-11 Wen-Xu Wang , Bo Hu , Bing-Hong Wang , Gang Yan
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