TY - GEN

T1 - Combinatorial miller–hagberg algorithm for randomization of dense networks

AU - Sayama, Hiroki

N1 - Publisher Copyright:
© Springer International Publishing AG 2018.

PY - 2018

Y1 - 2018

N2 - We propose a slightly revised Miller–Hagberg (MH) algorithm that efficiently generates a random network from a given expected degree sequence. The revision was to replace the approximated edge probability between a pair of nodes with a combinatorically calculated edge probability that better captures the likelihood of edge presence especially, where edges are dense. The computational complexity of this combinatorial MH algorithm is still in the same order as the original one. We evaluated the proposed algorithm through several numerical experiments. The results demonstrated that the proposed algorithm was particularly good at accurately representing high-degree nodes in dense, heterogeneous networks. This algorithm may be a useful alternative to other more established network randomization methods, given that the data are increasingly becoming larger and denser in today’s network science research.

AB - We propose a slightly revised Miller–Hagberg (MH) algorithm that efficiently generates a random network from a given expected degree sequence. The revision was to replace the approximated edge probability between a pair of nodes with a combinatorically calculated edge probability that better captures the likelihood of edge presence especially, where edges are dense. The computational complexity of this combinatorial MH algorithm is still in the same order as the original one. We evaluated the proposed algorithm through several numerical experiments. The results demonstrated that the proposed algorithm was particularly good at accurately representing high-degree nodes in dense, heterogeneous networks. This algorithm may be a useful alternative to other more established network randomization methods, given that the data are increasingly becoming larger and denser in today’s network science research.

UR - http://www.scopus.com/inward/record.url?scp=85054712144&partnerID=8YFLogxK

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U2 - 10.1007/978-3-319-73198-8_6

DO - 10.1007/978-3-319-73198-8_6

M3 - Conference contribution

AN - SCOPUS:85054712144

SN - 9783319731971

T3 - Springer Proceedings in Complexity

SP - 65

EP - 73

BT - Springer Proceedings in Complexity

A2 - Cornelius, Sean

A2 - Coronges, Kate

A2 - Goncalves, Bruno

A2 - Sinatra, Roberta

A2 - Vespignani, Alessandro

PB - Springer Science and Business Media B.V.

T2 - 9th International Conference on Complex Networks, CompleNet 2018

Y2 - 5 March 2018 through 8 March 2018

ER -