The effect of generalized deactivation mechanism in weighted networks

Liang Tian; Da-Ning Shi; Chen-Ping Zhu

doi:10.1016/j.physa.2007.02.104

The effect of generalized deactivation mechanism in weighted networks

Liang Tian, Da-Ning Shi^*, Chen-Ping Zhu

^*Corresponding author for this work

Department of Physics

Research output: Contribution to journal › Journal article › peer-review

4 Citations (Scopus)

Abstract

In this paper, we propose a generalized deactivation model to characterize weighted networks. By introducing the special aging mechanism, the model can produce power-law distributions of degree, strength, and weight, as confirmed in many real networks. We also characterize the clustering and correlation properties of this class of networks. A scaling behavior of clustering coefficient C ∼ 1 / M is observed, where M refers to the number of active nodes. The generated network simultaneously exhibits hierarchical organization and disassortative degree correlation. All of these structural properties are confirmed by present empirical evidence.

Original language	English
Pages (from-to)	611-620
Number of pages	10
Journal	Physica A: Statistical Mechanics and its Applications
Volume	380
Early online date	12 Mar 2007
DOIs	https://doi.org/10.1016/j.physa.2007.02.104
Publication status	Published - Jul 2007

User-Defined Keywords

Aging
Complex network
Generalized deactivation model
Weighted network

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10.1016/j.physa.2007.02.104

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title = "The effect of generalized deactivation mechanism in weighted networks",

abstract = "In this paper, we propose a generalized deactivation model to characterize weighted networks. By introducing the special aging mechanism, the model can produce power-law distributions of degree, strength, and weight, as confirmed in many real networks. We also characterize the clustering and correlation properties of this class of networks. A scaling behavior of clustering coefficient C ∼ 1 / M is observed, where M refers to the number of active nodes. The generated network simultaneously exhibits hierarchical organization and disassortative degree correlation. All of these structural properties are confirmed by present empirical evidence.",

keywords = "Aging, Complex network, Generalized deactivation model, Weighted network",

author = "Liang Tian and Da-Ning Shi and Chen-Ping Zhu",

note = "Funding Information: We thank the program for New Century Excellent Talents at University of China under (NECT-04-0510) and the National Natural Science Foundation of China under Grant Nos. 70471084 and 10372045 for financial supports.",

year = "2007",

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T1 - The effect of generalized deactivation mechanism in weighted networks

AU - Tian, Liang

AU - Shi, Da-Ning

AU - Zhu, Chen-Ping

N1 - Funding Information: We thank the program for New Century Excellent Talents at University of China under (NECT-04-0510) and the National Natural Science Foundation of China under Grant Nos. 70471084 and 10372045 for financial supports.

PY - 2007/7

Y1 - 2007/7

N2 - In this paper, we propose a generalized deactivation model to characterize weighted networks. By introducing the special aging mechanism, the model can produce power-law distributions of degree, strength, and weight, as confirmed in many real networks. We also characterize the clustering and correlation properties of this class of networks. A scaling behavior of clustering coefficient C ∼ 1 / M is observed, where M refers to the number of active nodes. The generated network simultaneously exhibits hierarchical organization and disassortative degree correlation. All of these structural properties are confirmed by present empirical evidence.

AB - In this paper, we propose a generalized deactivation model to characterize weighted networks. By introducing the special aging mechanism, the model can produce power-law distributions of degree, strength, and weight, as confirmed in many real networks. We also characterize the clustering and correlation properties of this class of networks. A scaling behavior of clustering coefficient C ∼ 1 / M is observed, where M refers to the number of active nodes. The generated network simultaneously exhibits hierarchical organization and disassortative degree correlation. All of these structural properties are confirmed by present empirical evidence.

KW - Aging

KW - Complex network

KW - Generalized deactivation model

KW - Weighted network

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U2 - 10.1016/j.physa.2007.02.104

DO - 10.1016/j.physa.2007.02.104

M3 - Journal article

AN - SCOPUS:34247869912

SN - 0378-4371

VL - 380

SP - 611

EP - 620

JO - Physica A: Statistical Mechanics and its Applications

JF - Physica A: Statistical Mechanics and its Applications

ER -

The effect of generalized deactivation mechanism in weighted networks

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