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Densification and structural transitions in networks that grow by node copying

Abstract:

We introduce a growing network model, the copying model, in which a new node attaches to a randomly selected target node and, in addition, independently to each of the neighbors of the target with copying probability p. When p<1/2, this algorithm generates sparse networks, in which the average node degree is finite. A power-law degree distribution also arises, with a nonuniversal exponent whose value is determined by a transcendental equation in p. In the sparse regime, the network is "nor...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1103/physreve.94.062302

Authors


Krapivsky, PL More by this author
More by this author
Department:
Oxford, MPLS, Mathematical Institute
Publisher:
American Physical Society Publisher's website
Journal:
Physical Review E Journal website
Volume:
94
Issue:
6
Pages:
Article: 062302
Publication date:
2016-12-08
Acceptance date:
2016-11-17
DOI:
EISSN:
2470-0053
ISSN:
2470-0045
Pubs id:
pubs:729442
URN:
uri:c008a583-6490-41e9-89ce-36d49632d35f
UUID:
uuid:c008a583-6490-41e9-89ce-36d49632d35f
Local pid:
pubs:729442
Language:
English
Keywords:

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