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Knoke and Yang's handy primer on social network analysis offers a concise introduction to basic network concepts, data collection, and network analytical methodology.
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Knoke and Yang's handy primer on social network analysis offers a concise introduction to basic network concepts, data collection, and network analytical methodology.
Produktdetails
- Produktdetails
- Quantitative Applications in the Social Sciences
- Verlag: SAGE Publications Inc
- 3 Revised edition
- Seitenzahl: 200
- Erscheinungstermin: 20. Januar 2020
- Englisch
- Abmessung: 213mm x 135mm x 13mm
- Gewicht: 240g
- ISBN-13: 9781506389318
- ISBN-10: 1506389317
- Artikelnr.: 57630328
- Quantitative Applications in the Social Sciences
- Verlag: SAGE Publications Inc
- 3 Revised edition
- Seitenzahl: 200
- Erscheinungstermin: 20. Januar 2020
- Englisch
- Abmessung: 213mm x 135mm x 13mm
- Gewicht: 240g
- ISBN-13: 9781506389318
- ISBN-10: 1506389317
- Artikelnr.: 57630328
David Knoke (Ph.D., University of Michigan, 1972) is a professor of sociology at the University of Minnesota, where he teaches and does research on diverse social networks, including political, economic, healthcare, intra- and interorganizational, and terrorist & counterterror networks. In addition to many articles and chapters, he has written seven books about networks: Network Analysis (1982, with James Kuklinski), The Organizational State (1985, with Edward Laumann), Political Networks (1990), Comparing Policy Networks (1996, with Franz Pappi, Jeffrey Broadbent, and Yutaka Tsujinaka), Changing Organizations (2001), Social Network Analysis (2008, with Song Yang), and Economic Networks (2012).
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
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
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
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