Description
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.
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.
