Abstract
While the emergence of a power-law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the betweenness centrality displays a power-law distribution with an exponent η, which is robust, and use it to classify the scale-free networks. We have observed two universality classes with η ≈ 2.2(1) and 2.0, respectively. Real-world networks for the former are the protein-interaction networks, the metabolic networks for eukaryotes and bacteria, and the coauthorship network, and those for the latter one are the Internet, the World Wide Web, and the metabolic networks for Archaea. Distinct features of the mass-distance relation, generic topology of geodesics, and resilience under attack of the two classes are identified. Various model networks also belong to either of the two classes, while their degree exponents are tunable.
| Original language | English |
|---|---|
| Pages (from-to) | 12583-12588 |
| Number of pages | 6 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Volume | 99 |
| Issue number | 20 |
| DOIs | |
| Publication status | Published - 2002 Oct 1 |
| Externally published | Yes |
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ASJC Scopus subject areas
- General
- Genetics
Cite this
Classification of scale-free networks. / Goh, Kwang-Il; Oh, Eulsik; Jeong, Hawoong; Kahng, Byungnam; Kim, Doochul.
In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, No. 20, 01.10.2002, p. 12583-12588.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Classification of scale-free networks
AU - Goh, Kwang-Il
AU - Oh, Eulsik
AU - Jeong, Hawoong
AU - Kahng, Byungnam
AU - Kim, Doochul
PY - 2002/10/1
Y1 - 2002/10/1
N2 - While the emergence of a power-law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the betweenness centrality displays a power-law distribution with an exponent η, which is robust, and use it to classify the scale-free networks. We have observed two universality classes with η ≈ 2.2(1) and 2.0, respectively. Real-world networks for the former are the protein-interaction networks, the metabolic networks for eukaryotes and bacteria, and the coauthorship network, and those for the latter one are the Internet, the World Wide Web, and the metabolic networks for Archaea. Distinct features of the mass-distance relation, generic topology of geodesics, and resilience under attack of the two classes are identified. Various model networks also belong to either of the two classes, while their degree exponents are tunable.
AB - While the emergence of a power-law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the betweenness centrality displays a power-law distribution with an exponent η, which is robust, and use it to classify the scale-free networks. We have observed two universality classes with η ≈ 2.2(1) and 2.0, respectively. Real-world networks for the former are the protein-interaction networks, the metabolic networks for eukaryotes and bacteria, and the coauthorship network, and those for the latter one are the Internet, the World Wide Web, and the metabolic networks for Archaea. Distinct features of the mass-distance relation, generic topology of geodesics, and resilience under attack of the two classes are identified. Various model networks also belong to either of the two classes, while their degree exponents are tunable.
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UR - http://www.scopus.com/inward/citedby.url?scp=0036792011&partnerID=8YFLogxK
U2 - 10.1073/pnas.202301299
DO - 10.1073/pnas.202301299
M3 - Article
C2 - 12239345
AN - SCOPUS:0036792011
VL - 99
SP - 12583
EP - 12588
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
SN - 0027-8424
IS - 20
ER -