Analyzing Social Networks2e By Stephen P. Borgatti
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Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process—including basic maths principles—without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way.
In addition to the fundamentals of network analysis and the research process, this Second Edition focuses on:
Digital data and social networks like Twitter
Statistical models to use in SNA, like QAP and ERGM
The structure and centrality of networks
Methods for cohesive subgroups/community detection
Supported by new chapter exercises, a glossary, and a fully updated companion website, this text is the perfect student-friendly introduction to social network analysis.
Chapter 1: Introduction
Chapter 2: Mathematical Foundations
Chapter 3: Research Design
Chapter 4: Data Collection
Chapter 5: Data Management
Chapter 6: Multivariate Techniques Used in Network Analysis
Chapter 7: Visualization
Chapter 8: Testing Hypotheses
Chapter 9: Characterizing Whole Networks
Chapter 10: Centrality
Chapter 11: Subgroups
Chapter 12: Equivalence
Chapter 13: Analyzing Two-mode Data
Chapter 14: Large Networks
Chapter 15: Ego Networks
In addition to the fundamentals of network analysis and the research process, this Second Edition focuses on:
Digital data and social networks like Twitter
Statistical models to use in SNA, like QAP and ERGM
The structure and centrality of networks
Methods for cohesive subgroups/community detection
Supported by new chapter exercises, a glossary, and a fully updated companion website, this text is the perfect student-friendly introduction to social network analysis.
Chapter 1: Introduction
Chapter 2: Mathematical Foundations
Chapter 3: Research Design
Chapter 4: Data Collection
Chapter 5: Data Management
Chapter 6: Multivariate Techniques Used in Network Analysis
Chapter 7: Visualization
Chapter 8: Testing Hypotheses
Chapter 9: Characterizing Whole Networks
Chapter 10: Centrality
Chapter 11: Subgroups
Chapter 12: Equivalence
Chapter 13: Analyzing Two-mode Data
Chapter 14: Large Networks
Chapter 15: Ego Networks
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