Full Description
The size and availability of network information has exploded over the last decade. Social scientists now share the stage of network analysis with computer scientists, physicists, and statisticians. While a number of introductions to network analysis are now available, most focus on theory, methods, or application alone. This book integrates all three. Network Analysis is an introduction to both the why and how of Social Network Analysis (SNA). It presents a broad theoretical overview rooted in social scientific approaches and guides users in how network analysis can answer core theoretical questions. It provides a comprehensive overview of descriptive and analytical approaches, including practical tutorials in R with sample data sets. Using an integrated approach, this book aims to quickly bring novice network researchers up to speed while avoiding common programming and analysis mistakes so that they might gain insight into the fundamental theories, key concepts, and methodological application of SNA.
Contents
Introduction; 1. Network analysis today; Part I. Thinking Structurally: 2. What is social structure?; 3. What is a social network?; 4. How are social network data collected?; 5. How are social network data visualized?; Part II. Seeing Structure: 6. Structuration and ego-centric networks; 7. Sociality and elementary forms of structure; 8. Cohesion and groups; 9. Hierarchy and centrality; 10. Positions and roles; 11. Affiliations and dualities; 12. Networks and culture; Part III. Making Structural Predictions: 13. Models for networks; 14. Models for network diffusion; 15. Models for social influence; Conclusion: 16. Network analysis tomorrow.
