The Sage Handbook of Social Network Analysis Review
The Sage Handbook of Social Network Analysis, edited by John Scott and Peter J. Carrington, is a comprehensive survey of SNA theory, methods, and applications. It maps the field from foundational concepts to advanced models and diverse domains. Treat it as both a reference and a curriculum.
Overview
Chapters cover graph concepts, data collection, ego and whole networks, centrality and cohesion, blockmodeling, statistical network models, longitudinal change, and applications across sociology, organizations, health, crime, and policy. Method, software, and design issues are treated with breadth.
Summary
The volume aligns concepts (ties, multiplexity, homophily, brokerage) with tools: matrix methods, community detection, exponential random graph models (ERGMs), stochastic actor-oriented models (SAOM), and multilevel designs. Case chapters show how network structure shapes outcomes in diffusion, collaboration, governance, and risk.
Authors
Scott and Carrington assemble leading contributors. The tone is rigorous yet accessible, with clear bibliographies to deepen each topic.
Key Themes
Structure explains behavior; measurement choices matter; inference is constrained by dependence; longitudinal data reveal mechanisms, not just snapshots.
Strengths and Weaknesses
Strengths: authoritative scope, balanced methods, and application range. Weaknesses: uneven chapter depth and limited hands-on code. Pair with software guides for implementation.
Target Audience
Researchers, graduate students, and analysts who need a field map and pointers to specialized methods.
Favorite Ideas
Bridging structural holes for advantage; multiplex networks that couple roles and resources; design-based sampling for hard-to-reach networks.
Takeaways
Choose measures and models that match mechanisms and data. Combine descriptive structure with estimable models, especially for change over time.
