Social Network Analysis
Third Edition
David Knoke
- University of Minnesota, USA
Song Yang
- University of Arkansas, USA
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Go to College Publishing WebsiteDescription
David 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a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs.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.
Contents
Series Editor’s Introduction
Series Editor’s Introduction
About the Authors
About the Authors
Acknowledgments
Acknowledgments
Chapter 1. Introduction to Social Network Analysis
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
Appendix: Social Network Analysis Software Packages
References
References
Index
Index
Additional materials
Description
David 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.
Contents
Series Editor’s Introduction
Series Editor’s Introduction
About the Authors
About the Authors
Acknowledgments
Acknowledgments
Chapter 1. Introduction to Social Network Analysis
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
Appendix: Social Network Analysis Software Packages
References
References
Index
Index
Additional materials
Reviews
December 2019 | 200 pages | Sage US
| Format | Published Date | ISBN | Price |
|---|
David 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.
Table Of Contents:
- Series 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
Recent Product Reviews:
One of the most clear and yet comprehensive explanations of network analysis in research that I have ever read.
Howard Lune, Hunter College, CUNY
This book provides a solid foundation for conducting a social network analysis for all analytics professionals
Michael Levin, Otterbein University
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, RTI International and Duke University