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Multilayer Social Networks

Book 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. Cover
  2. Half title
  3. Title
  4. Copyright
  5. Dedication
  6. Table of Contents
  7. List of Abbreviations
  8. 1 Moving Out of Flatland
    1. 1.1 Multiple Social Networks in Our Everyday Experience
    2. 1.2 An Introductory Example
    3. 1.3 Scope and Other Learning Resources
    4. 1.4 Outline of the Book
    5. 1.5 Acknowledgments
  9. Part I Models and Measures
    1. 2 Representing Multilayer Social Networks
      1. 2.1 Terminology and Model
      2. 2.2 Related Models
      3. 2.3 Data Sets
    2. 3 Measuring Multilayer Social Networks
      1. 3.1 Four Main Approaches
      2. 3.2 Actor Measures
      3. 3.3 Layer Measures
  10. Part II Mining Multilayer Networks
    1. 4 Data Collection and Preprocessing
      1. 4.1 Issues in Data Collection
      2. 4.2 Network Simplification
    2. 5 Visualizing Multilayer Networks
      1. 5.1 Four Main Approaches
      2. 5.2 Visualizing Multilayer Network Metrics
      3. 5.3 Visualizing Multilayer Network Structures
      4. 5.4 Augmented Networks: Structure + Measures
      5. 5.5 Simplified Network Visualization
    3. 6 Community Detection
      1. 6.1 Methods Based on Simplification
      2. 6.2 Combination of Single-Layer Communities
      3. 6.3 Multilayer Modularity Optimization
      4. 6.4 Multiple Actor Types
      5. 6.5 Community Interpretation, Evaluation, and Description
    4. 7 Edge Patterns
      1. 7.1 Edge Prediction
      2. 7.2 Layer Associativity
  11. Part III Dynamical Processes
    1. 8 Formation of Multilayer Social Networks
      1. 8.1 General Properties for Social Network Formation
      2. 8.2 Single-Layer Network Formation
      3. 8.3 Multilayer Properties
      4. 8.4 Multilayer Formation Models
    2. 9 Information and Behavior Diffusion
      1. 9.1 Diffusion in Networks
      2. 9.2 Modeling Information Spreading
      3. 9.3 Opinion Formation and Behavior Adaptation
  12. Part IV Conclusion
    1. 10 Future Directions
      1. 10.1 New Models and Measures
      2. 10.2 Multilayer Network Visualization
      3. 10.3 Communities and Other Groups
      4. 10.4 Formation, Diffusion, and Temporal Processes
      5. 10.5 Big Open Data
  13. Glossary
  14. Bibliography
  15. Index