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Many complex natural and physical systems exhibit patterns of interconnection that conform, approximately, to a network structure referred to as scale-free. Preferential attachment is one of many algorithms that have been introduced to…

物理与社会 · 物理学 2014-11-18 Linjun Zhang , Michael Small , Kevin Judd

Many complex systems--from social and communication networks to biological networks and the Internet--are thought to exhibit scale-free structure. However, prevailing explanations rely on the constant addition of new nodes, an assumption…

适应与自组织系统 · 物理学 2022-11-10 Christopher W. Lynn , Caroline M. Holmes , Stephanie E. Palmer

A new mechanism leading to scale-free networks is proposed in this letter. It is shown that in many cases of interest, the connectivity power-law behavior is neither related to dynamical properties nor to preferential attachment. Instead,…

无序系统与神经网络 · 物理学 2007-05-23 G. Caldarelli , A. Capocci , P. De Los Rios , M. A. Munoz

A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree $k$ follows a power law, decaying like $k^{-\alpha}$, often with $2 < \alpha < 3$. However,…

物理与社会 · 物理学 2019-03-19 Anna D. Broido , Aaron Clauset

We show that not only preferential attachment but also preferential depletion leads to scale-free networks. The resulting degree distribution exponents is typically less than two (5/3) as opposed to the case of the growth models studied…

物理与社会 · 物理学 2015-05-27 Christian M. Schneider , Lucilla de Arcangelis , Hans J. Herrmann

Scale-free networks with small power law exponent are known to be robust, meaning that their qualitative topological structure cannot be altered by random removal of even a large proportion of nodes. By contrast, it has been argued in the…

概率论 · 数学 2013-08-23 Maren Eckhoff , Peter Mörters

Preferential attachment --- by which new nodes attach to existing nodes with probability proportional to the existing nodes' degree --- has become the standard growth model for scale-free networks, where the asymptotic probability of a node…

适应与自组织系统 · 物理学 2014-11-12 Michael Small , Yingying Li , Thomas Stemler , Kevin Judd

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…

物理与社会 · 物理学 2015-06-11 Boris Podobnik , Davor Horvatic , Mark Dickison , H. Eugene Stanley

Preferential attachment is one possible way to obtain a scale-free network. We develop a self-consistent method to determine whether preferential attachment occurs during the growth of a network, and to extract the preferential attachment…

统计力学 · 物理学 2007-05-23 Claire P. Massen , Jonathan P. K. Doye

It is commonly believed that scale-free networks are robust to massive numbers of random node deletions. For example, Cohen et al. study scale-free networks including some which approximate the measured degree distribution of the Internet.…

网络与互联网体系结构 · 计算机科学 2007-05-23 Hamilton Link , Randall A. LaViolette , Jared Saia , Terran Lane

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…

统计力学 · 物理学 2009-11-07 R. Xulvi-Brunet , I. M. Sokolov

Many realistic networks are scale-free, with small characteristic path lengths, high clustering, and power law in their degree distribution. They can be obtained by dynamical networks in which a preferential attachment process takes place.…

物理与社会 · 物理学 2017-03-13 Francesco Caravelli , Alioscia Hamma , Massimiliano Di Ventra

Many real networks such as the World Wide Web, financial, biological, citation and social networks have a power-law degree distribution. Networks with this feature are also called scale-free. Several models for producing scale-free networks…

社会与信息网络 · 计算机科学 2016-12-23 Akmal Artikov , Aleksandr Dorodnykh , Yana Kashinskaya , Egor Samosvat

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…

The structure of complex networks in previous research has been widely described as scale-free networks generated by the preferential attachment model. However, the preferential attachment model does not take into account the detailed…

无序系统与神经网络 · 物理学 2008-02-26 Nobuhiko Oshida , Sigeo Ihara

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

In this paper, we present a simple model of scale-free networks that incorporates both preferential & random attachment and anti-preferential & random deletion at each time step. We derive the degree distribution analytically and show that…

数据分析、统计与概率 · 物理学 2007-05-23 Dinghua Shi , Xiang Zhu , Liming Liu

While previous works have shown that an overwhelming number of scale-free networks are sparse, there still exist some real-world networks including social networks, urban networks, information networks, which are by observation dense. In…

社会与信息网络 · 计算机科学 2020-10-29 Fei Ma , Xiaomin Wang , Ping Wang , Xudong Luo

Network growth is currently explained through mechanisms that rely on node prestige measures, such as degree or fitness. In many real networks those who create and connect nodes do not know the prestige values of existing nodes, but only…

无序系统与神经网络 · 物理学 2007-05-23 Santo Fortunato , Alessandro Flammini , Filippo Menczer

It has been well-known that many real networks are scale-free (SF) but extremely vulnerable against attacks. We investigate the robustness of connectivity and the lengths of the shortest loops in randomized SF networks with realistic…

社会与信息网络 · 计算机科学 2026-02-03 Yingzhou Mou , Yukio Hayashi
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