Taking network analysis to the next step, multilayer networks are sets of different networks that interact among themselves or networks that change dynamically over time (or combinations of the two). As layers interact, links that denote stronger connections can lead to chain events and catastrophic impacts. Capturing this type of behavior allows multilayer networks to model complex systems. Not to be confused with subnetworks in a larger network, the layers in multilayer architectures tend to be different from each other.
The book starts with the basics of single-layer networks but quickly moves into more challenging multilayer network concepts. Math that may seem complex at first is mostly sums and products (some with quite complex nesting). There are also elements of more challenging linear algebra and bits of calculus here and there.
The book is illustrated with a wealth of charts, some in color, which are especially useful in depicting complex multidimensional network diagrams. The few hundred references are all clustered at the end of the book, before a rather small index.
Throughout the book, it is readily apparent what a wide range of applications there are for multilayer network models, including in social sciences, finance, transportation, ecology and brain science. Compared with those on other, more established topics, only relatively few books have been published on multilayer networks so far. This book is an excellent reference for professionals or a great choice of textbook (aside from not having application problems that can be assigned to students).
Review by Bogdan Hoanca, University of Alaska Anchorage, USA.
The opinions expressed in the book review section are those of the reviewer and do not necessarily reflect those of OPN or its publisher, Optica (formerly OSA).