This self-contained book systematically explores the statistical dynamics on and of complex networks with a special focus on time-varying networks. In the constantly changing modern world, there is an urgent need to understand problems related to systems that dynamically evolve in either structure or function, or both. This work is an attempt to address such problems in the framework of complex networks.

Dynamics on and of Complex Networks, Volume 2: Applications to Time-Varying Dynamical Systems is a collection of surveys and cutting-edge research contributions exploring key issues, challenges, and characteristics of dynamical networks that emerge in various complex systems. Toward this goal, the work is thematically organized into three main sections with the primary thrust on time-varying networks: Part I studies social dynamics; Part II focuses on community identification; and Part III illustrates diffusion processes.

The contributed chapters in this volume are intended to promote cross-fertilization in several research areas and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in pursuing research in dynamical networks with applications to computer science, statistical physics, nonlinear dynamics, linguistics, and the social sciences.

This volume follows Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences (2009), ISBN 978-0-8176-4750-6.

Contenuti:

Part I Online social media, Internet and WWW.- Dynamics in online social networks.- An empirical validation of growth models for complex networks.- On the routability of the Internet.- The evolution of layered protocol stacks leads to an hourglass-shaped architecture.- Opinion dynamics on coevolving networks.- Part II Community analysis.- A template for parallelizing the Louvain method for modularity Maximization.- Multi-scale modularity and dynamics in complex networks.- Evaluating the performance of clustering algorithms in networks.- Communities in evolving networks: definitions, detection and analysis Techniques.- Clustering hypergraphs for discovery of overlapping communities in folksonomies.- The stability of a graph partition: A dynamics-based framework for community detection.- Algorithms for finding motifs in large labeled networks.- Part III Diffusion, spreading, mobility and transport.- A dynamical network view of Lyon’s V�elo’v shared bicycle System.- Generalized voter-like models on heterogeneous networks.- Epidemics on a stochastic model of temporal network.- Network-based information filtering algorithms: ranking and recommendation

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