The European Physical Journal Special Topics

, Volume 226, Issue 3, pp 401–416

The new challenges of multiplex networks: Measures and models

  • Federico Battiston
  • Vincenzo Nicosia
  • Vito Latora
Open Access
Regular Article

DOI: 10.1140/epjst/e2016-60274-8

Cite this article as:
Battiston, F., Nicosia, V. & Latora, V. Eur. Phys. J. Spec. Top. (2017) 226: 401. doi:10.1140/epjst/e2016-60274-8
Part of the following topical collections:
  1. Nonlinearity, Nonequilibrium and Complexity: Questions and Perspectives in Statistical Physics


What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons, rather than only by the properties of the units themselves. In the last two decades, network scientists have proposed models of increasing complexity to better understand real-world systems. Only recently we have realised that multiplexity, i.e. the coexistence of several types of interactions among the constituents of a complex system, is responsible for substantial qualitative and quantitative differences in the type and variety of behaviours that a complex system can exhibit. As a consequence, multilayer and multiplex networks have become a hot topic in complexity science. Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance. Focusing on a subset of relevant topics, this brief review is a quite comprehensive introduction to the most basic tools for the analysis of multiplex networks observed in the real-world. The wide applicability of multiplex networks as a framework to model complex systems in different fields, from biology to social sciences, and the colloquial tone of the paper will make it an interesting read for researchers working on both theoretical and experimental analysis of networked systems.

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© The Author(s) 2017

Open Access This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Federico Battiston
    • 1
  • Vincenzo Nicosia
    • 1
  • Vito Latora
    • 1
    • 2
  1. 1.School of Mathematical Sciences, Queen Mary University of LondonLondon E1 4NSUK
  2. 2.Dipartimento di Fisica ed Astronomia, Università di Catania and INFNCataniaItaly

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