Network Analysis
Integrating Social Network Theory, Method, and Application with R

A comprehensive yet accessible introduction to the theory, methods, and application of social network analysis.

Craig M. Rawlings (Author), Jeffrey A. Smith (Author), James Moody (Author), Daniel A. McFarland (Author)

9781107611900, Cambridge University Press

Paperback / softback, published 5 October 2023

476 pages
22.8 x 15.2 x 2.5 cm, 0.7 kg

'This book provides a wonderful integration of the theoretical and conceptual basis of social network analysis with modern methods. Traditional methods are not forgotten! The accompanying R tutorials are a great resource. The approach is original and convincing. The book offers excellent material for beginners, but also seasoned network researchers will learn a lot from it.' Tom Snijders, Universities of Groningen and Oxford

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.

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.

Subject Areas: Social research & statistics [JHBC]