Network science offers a powerful language to represent and study complex systems composed of interacting elements — from the Internet to social and biological systems. A Guide to Temporal Networks presents recent theoretical and modelling progress in the emerging field of temporally varying networks and provides connections between the different areas of knowledge required to address this multi-disciplinary subject. After an introduction to key concepts on networks and stochastic dynamics, the authors guide the reader through a coherent selection of mathematical and computational tools for network dynamics. Perfect for students and professionals, this book is a gateway to an active field of research developing between the disciplines of applied mathematics, physics and computer science, with applications in others including social sciences, neuroscience and biology. This second edition extensively expands upon the coverage of the first edition as the authors expertly present recent theoretical and modelling progress in the emerging field of temporal networks, providing the keys to (and connections between) the different areas of knowledge required to address this multi-disciplinary problem. Key Features: o There have been several books on networks and complex networks in recent years yet none of them have addressed the problems of temporal networks so far o This is a pedagogical and interdisciplinary book aimed at presenting important pre-requisites from different disciplines (graph theory, static complex networks, spectral graph theory, stochastic processes, non-equilibrium statistical physics, queuing theory) o Provides a comprehensive view of the field: main results and future challenges

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