Description
Book SynopsisDavid Knoke and Song Yang′s
Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of social network analysis. The authors convey key material while at the same time minimizing technical complexities. The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade. The new edition reflects developments and changes in practice over the past decade. The authors also describe important recent developments in network analysis, especially in the fifth chapter. Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.
Trade ReviewOne of the most clear and yet comprehensive explanations of network analysis in research that I have ever read.
-- Howard Lune * Review *
This book provides a solid foundation for conducting a social network analysis for all analytics professionals
-- Michael Levin * Review *
Knoke and Yang have written a compelling new edition that balances timeless description of key network concepts with a fresh set of examples drawn from the myriad instances in which social scientists are using social network analysis to understand relationships.
-- Brian G. Southwell * Review *
Table of ContentsSeries Editor’s Introduction About the Authors Acknowledgments Chapter 1. Introduction to Social Network Analysis Chapter 2. Network Fundamentals 2.1. Underlying Assumptions 2.2. Entities and Relations 2.3. Networks 2.4. Research Design Elements Chapter 3. Data Collection 3.1. Boundary Specification 3.2. Data Collection Procedures 3.3. Cognitive Social Structure 3.4. Missing Data 3.5. Measurement Error 3.6. Collecting Network Data Chapter 4. Basic Methods for Analyzing Networks 4.1. Network Representation: Graphs and Matrices 4.2. Nodes: Centrality, Power, Prestige 4.3. Dyads: Walk, Path, Distance, Reachability 4.4. Subgroups: Transitivity and Cliques 4.5. Whole Networks: Size, Density, Centralization 4.6. Structural, Regular, and Automorphic Equivalence Chapter 5. Advanced Methods for Analyzing Networks 5.1. Ego-Nets 5.2. Visualizations: Clustering, MDS, Blockmodels 5.3. Two-Mode and 3-Mode Networks 5.4. Community Detection 5.5. Exponential Random Graph Models (ERGMs) 5.6. Future Directions in Network Analysis Appendix: Social Network Analysis Software Packages References Index
