4.3 Article

Multilayer networks

Journal

JOURNAL OF COMPLEX NETWORKS
Volume 2, Issue 3, Pages 203-271

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/comnet/cnu016

Keywords

multilayer networks; dynamical systems on networks; models of networks; structural analysis of networks; mathematical analysis and simulations of networks; data analysis

Funding

  1. European Commission FET-Proactive project PLEXMATH [317614]
  2. ICREA Academia, Generalitat de Catalunya [2009-SGR-838]
  3. James S. McDonnell Foundation
  4. Science Foundation Ireland [11/PI/1026, 09/SRC/E1780]
  5. MINECO [FIS2011-25167]
  6. DGA (Spain)
  7. EPSRC [EP/J001759/1]
  8. [FIS2012-38266]
  9. EPSRC [EP/J001759/1] Funding Source: UKRI

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In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such 'multilayer' features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize 'traditional' network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other and provide a thorough discussion that compares, contrasts and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.

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