A degree-thresholding renormalization method is recently
introduced to find topological characteristics of some complex
networks. As a matter of fact, the applicability of these
characteristics depends on the level or the type of complex networks.
Here, a modified version of this original algorithm is presented to
unravel ubiquitous characteristics of observed email networks and
obtain correct understanding of underlying evolutionary mechanism.
Some topology metrics of the email networks under renormalization were
analyzed. The results show that renormalization email networks have
the power-law distribution with double exponents, are disassortative
and become assortative after half of total renormalization steps, have
high-clustering coefficients and richclub phenomena. These
characteristics are self-similar both before and after renormalization
until half of total renormalization steps, otherwise are
self-dissimilar.
%0 Book Section
%1 Zhang_2009
%A Zhang, Lianming
%A Liu, Sundong
%A Tang, Yuling
%A Xu, Hualan
%B Complex Sciences: First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1
%D 2009
%I Springer Berlin Heidelberg
%K assortativity, correlations, email, networks, scale-free,
%P 1846--1859
%T Correlation Properties and Self-similarity of Renormalization Email
Networks
%X A degree-thresholding renormalization method is recently
introduced to find topological characteristics of some complex
networks. As a matter of fact, the applicability of these
characteristics depends on the level or the type of complex networks.
Here, a modified version of this original algorithm is presented to
unravel ubiquitous characteristics of observed email networks and
obtain correct understanding of underlying evolutionary mechanism.
Some topology metrics of the email networks under renormalization were
analyzed. The results show that renormalization email networks have
the power-law distribution with double exponents, are disassortative
and become assortative after half of total renormalization steps, have
high-clustering coefficients and richclub phenomena. These
characteristics are self-similar both before and after renormalization
until half of total renormalization steps, otherwise are
self-dissimilar.
@inbook{Zhang_2009,
abstract = {A degree-thresholding renormalization method is recently
introduced to find topological characteristics of some complex
networks. As a matter of fact, the applicability of these
characteristics depends on the level or the type of complex networks.
Here, a modified version of this original algorithm is presented to
unravel ubiquitous characteristics of observed email networks and
obtain correct understanding of underlying evolutionary mechanism.
Some topology metrics of the email networks under renormalization were
analyzed. The results show that renormalization email networks have
the power-law distribution with double exponents, are disassortative
and become assortative after half of total renormalization steps, have
high-clustering coefficients and richclub phenomena. These
characteristics are self-similar both before and after renormalization
until half of total renormalization steps, otherwise are
self-dissimilar.},
added-at = {2010-05-10T08:12:01.000+0200},
author = {Zhang, Lianming and Liu, Sundong and Tang, Yuling and Xu, Hualan},
biburl = {https://www.bibsonomy.org/bibtex/21689a72d7333eac6fb7d4c8b0a40b7e8/dhruvbansal},
booktitle = {Complex Sciences: First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1},
file = {/home/dhruv/projects/work/papers/papers/Zhang_2009.pdf},
interhash = {7f9630e7a1dbb76b43806ae00ddcb371},
intrahash = {1689a72d7333eac6fb7d4c8b0a40b7e8},
keywords = {assortativity, correlations, email, networks, scale-free,},
pages = {1846--1859},
publisher = {Springer Berlin Heidelberg},
read = {nil},
series = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},
timestamp = {2010-05-10T08:12:07.000+0200},
title = {Correlation Properties and Self-similarity of Renormalization Email
Networks},
year = 2009
}