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Open AccessJournal ArticleDOI

Temporal fractal structures: origin of power laws in the world-wide Web

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TLDR
In this paper, the authors study the dynamics of the world-wide web from the growth rules recently proposed in Tadic (Physica A 293 (2001) 273) with appropriate parameters.
Abstract
Using numerical simulations and scaling theory we study the dynamics of the world-wide Web from the growth rules recently proposed in Tadic (Physica A 293 (2001) 273) with appropriate parameters. We demonstrate that the emergence of power-law behavior of the out- and in-degree distributions in the Web involves occurrence of temporal fractal structures that are manifested in the scale-free growth of the local connectivity and in first-return time statistics. We also show how the scale-free behavior occurs in the statistics of random walks on the Web, where the walkers use information on the local graph connectivity.

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Journal ArticleDOI

The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI

Complex networks: Structure and dynamics

TL;DR: The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
Journal ArticleDOI

Maximal planar networks with large clustering coefficient and power-law degree distribution.

TL;DR: It is proved that RANs are maximal planar networks, which are of particular practicability for layout of printed circuits and so on, and the diseases spread slower in R ANs than BA networks in the early stage of the susceptible-infected process, indicating that the large clustering coefficient may slow the spreading velocity.
Book ChapterDOI

Structural properties of scale‐free networks

TL;DR: The structural properties of scale-free networks are studied and it is shown that in the regime 2 < < 3 the networks are resilient to random breakdown and the percolation transition occurs only in the limit of extreme dilution.
Journal ArticleDOI

Exact solutions for models of evolving networks with addition and deletion of nodes.

TL;DR: Here models of the time evolution of networks that grow by the addition of vertices and so-called preferential attachment are formulated and it is conjecture that the low exponent values observed in real-world networks are the result of vigorous growth, which far exceeds the rate of removal.
References
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Journal ArticleDOI

Statistical mechanics of complex networks

TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Journal ArticleDOI

Exploring complex networks

TL;DR: This work aims to understand how an enormous network of interacting dynamical systems — be they neurons, power stations or lasers — will behave collectively, given their individual dynamics and coupling architecture.
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The large-scale organization of metabolic networks

TL;DR: In this paper, the authors present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life, and show that despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems.

The large-scale organization of metabolic networks

TL;DR: This analysis of metabolic networks of 43 organisms representing all three domains of life shows that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems.
Journal ArticleDOI

Graph structure in the Web

TL;DR: The study of the web as a graph yields valuable insight into web algorithms for crawling, searching and community discovery, and the sociological phenomena which characterize its evolution.