Multilayer Social Networks

This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing.

Mark E. Dickison (Author), Matteo Magnani (Author), Luca Rossi (Author)

9781107079496, Cambridge University Press

Hardback, published 19 July 2016

188 pages
23.5 x 15.7 x 1.5 cm, 0.42 kg

'This is a comprehensive guide to a fascinating mathematical and computational perspective on real-world social phenomena … Overall, the book provides a thorough introduction to multilayer social networks, followed by an extensive literature review. The intensive interest and the enthusiasm of the authors for this area are contagious and stimulate the readers to further explore multilayer networks as tools for their own research domains. Hence, the book is recommended to researchers, practitioners, and teachers who are eager to 'escape from Flatland' and investigate new dimensions.' Lefteris Angelis, Computing Reviews

Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate research communities, leading to the development of several independent models and methods to deal with the same set of problems. This book unifies and consolidates existing practical and theoretical knowledge on multilayer networks including data collection and analysis, modeling, and mining of multilayer social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various methods. Researchers from all areas of network analysis will learn new aspects and future directions of this emerging field.

1. Moving out of flatland
Part I. Models and Measures: 2. Representing multilayer social networks
3. Measuring multilayer social networks
Part II. Mining Multilayer Networks: 4. Data collection and preprocessing
5. Visualizing multilayer networks
6. Community detection
7. Edge patterns
Part III. Dynamical Processes: 8. Formation of multilayer social networks
9. Information and behavior diffusion
Part IV. Conclusion: 10. Future directions.

Subject Areas: Ethical & social aspects of IT [UBJ], Statistical physics [PHS], Probability & statistics [PBT], Social research & statistics [JHBC]