Abstract
Typical complex system operates through multiple types of interactions between its constituents. The collective function of these multiple interactions, or multiple network layers, is often non-additive, resulting in nontrivial effects on the network structure and dynamics. To better model such situations, the concept of multiplex network, the network with explicit multiple types of links, has recently been applied. In this contribution, we survey recent studies on this subject, focused on the notion of correlated multiplexity. Empirical multiplex network analysis as well as analytical results on the random graph models of correlated multiplex networks are presented, followed by a brief summary of dynamical processes on multiplex networks. It is illustrated that a multiplex complex system can indeed exhibit structural and dynamical properties that cannot be represented by its individual layer's properties alone, establishing the network multiplexity as an essential ingredient in the new physics of "network of networks."
| Original language | English |
|---|---|
| Title of host publication | Understanding Complex Systems |
| Pages | 53-72 |
| Number of pages | 20 |
| DOIs | |
| Publication status | Published - 2014 Mar 12 |
Publication series
| Name | Understanding Complex Systems |
|---|---|
| ISSN (Print) | 18600832 |
| ISSN (Electronic) | 18600840 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Computational Mechanics
- Software
Cite this
Multiplex networks. / Lee, Kyu Min; Kim, Jung Yeol; Lee, Sangchul; Goh, Kwang-Il.
Understanding Complex Systems. 2014. p. 53-72 (Understanding Complex Systems).Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Multiplex networks
AU - Lee, Kyu Min
AU - Kim, Jung Yeol
AU - Lee, Sangchul
AU - Goh, Kwang-Il
PY - 2014/3/12
Y1 - 2014/3/12
N2 - Typical complex system operates through multiple types of interactions between its constituents. The collective function of these multiple interactions, or multiple network layers, is often non-additive, resulting in nontrivial effects on the network structure and dynamics. To better model such situations, the concept of multiplex network, the network with explicit multiple types of links, has recently been applied. In this contribution, we survey recent studies on this subject, focused on the notion of correlated multiplexity. Empirical multiplex network analysis as well as analytical results on the random graph models of correlated multiplex networks are presented, followed by a brief summary of dynamical processes on multiplex networks. It is illustrated that a multiplex complex system can indeed exhibit structural and dynamical properties that cannot be represented by its individual layer's properties alone, establishing the network multiplexity as an essential ingredient in the new physics of "network of networks."
AB - Typical complex system operates through multiple types of interactions between its constituents. The collective function of these multiple interactions, or multiple network layers, is often non-additive, resulting in nontrivial effects on the network structure and dynamics. To better model such situations, the concept of multiplex network, the network with explicit multiple types of links, has recently been applied. In this contribution, we survey recent studies on this subject, focused on the notion of correlated multiplexity. Empirical multiplex network analysis as well as analytical results on the random graph models of correlated multiplex networks are presented, followed by a brief summary of dynamical processes on multiplex networks. It is illustrated that a multiplex complex system can indeed exhibit structural and dynamical properties that cannot be represented by its individual layer's properties alone, establishing the network multiplexity as an essential ingredient in the new physics of "network of networks."
UR - http://www.scopus.com/inward/record.url?scp=84897732756&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897732756&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-03518-5-3
DO - 10.1007/978-3-319-03518-5-3
M3 - Chapter
SN - 9783319035178
T3 - Understanding Complex Systems
SP - 53
EP - 72
BT - Understanding Complex Systems
ER -