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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.Read more
- Unifies knowledge from separate disciplines
- The use of real datasets shows the practical usability of the methods
- Accessible to readers with different backgrounds, from social science through to physics
Reviews & endorsements
'A well-crafted and clear exposition of the important area of multilayer social networks. The authors skillfully entwine theory and applications to produce a highly readable account of recent research in this ever expanding field. A must have for any network scientist.' Martin Everett, University of ManchesterSee more reviews
'A wonderful compendium of methods for multivariate - multirelational, multimodal, multiplex, etc. - networks, focusing on extensions of traditional techniques (subgroups, centrality, clustering, and visualizing). Buy this book and use it! Cambridge University Press remains at the forefront of publishing network science books.' Stanley Wasserman, Indiana University, Bloomington, and National Research University Higher School of Economics, Moscow
'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
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- Date Published: July 2016
- format: Paperback
- isbn: 9781107438750
- length: 208 pages
- dimensions: 229 x 152 x 12 mm
- weight: 0.32kg
- availability: In stock
Table of Contents
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.
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