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Social network analysis with applications /
Authored by military and intelligence professionals, this book introduces the new and emerging topic of social network analysis. Focusing on models and methods for the analysis of organizational risk, the book provides easily accessible yet comprehensive coverage of networks basics, basic centrality...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
John Wiley & Sons, Inc.,
[2013]
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- part I. Network basics. chapter 1. What is a network? ; chapter 2. Centrality measures ; chapter 3. Graph level measures
- part II. Social theory. chapter 4. Social links ; chapter 5. Subgroup analysis ; chapter 6. Diffusion and influence
- part III. Data. chapter 7. Meta-networks and relational algebra ; chapter 8. Sources of data
- part IV. Organizational risk. chapter 9. Organizational risk
- appendix A. Matrix algebra primer
- appendix B. Tables of data and networks
- appendix C. Five points of a graph.
- SOCIAL NETWORK ANALYSIS; CONTENTS; LIST OF FIGURES; LIST OF TABLES; FOREWORD; PREFACE; ACKNOWLEDGMENTS; INTRODUCTION; PART I NETWORK BASICS; CHAPTER 1 WHAT IS A NETWORK?; 1.1 Basic Network Concepts; 1.2 Adjacency Matrices, Graphs, and Notation; 1.3 Nodes and Links; 1.4 Good Will Hunting Problem; 1.5 Formal and Informal Networks; 1.6 Summary; Chapter 1 Lab Exercise; Exercises; References; CHAPTER 2 CENTRALITY MEASURES; 2.1 What is ""Centrality"" and Why do we Study IT?; 2.2 Calculating Nodal Centrality Measures; 2.2.1 Degree Centrality; 2.2.2 Betweenness Centrality; 2.2.3 Closeness Centrality.
- 2.2.4 Eigenvector Centrality2.2.5 Google PageRank: A Variant of Eigenvector Centrality; 2.3 Directed Networks and Centrality Measures; 2.4 Location in the Network; 2.5 Summary; Chapter 2 Lab Exercise; Exercises; References; CHAPTER 3 GRAPH LEVEL MEASURES; 3.1 Density; 3.2 Diameter; 3.3 Centralization; 3.3.1 Degree Centralization; 3.3.2 Betweenness Centralization; 3.3.3 Closeness Centralization; 3.4 Average Centralities; 3.5 Network Topology; 3.5.1 Lattice Networks; 3.5.2 Small World Networks; 3.5.3 Core Periphery; 3.5.4 Cellular Networks; 3.5.5 Scale-Free Networks.
- 3.5.6 Random (Erdös-Rényi) Networks3.5.7 Comparison of Network Topologies; 3.6 Summary; Chapter 3 Lab Exercise; Exercises; References; PART II SOCIAL THEORY; CHAPTER 4 SOCIAL LINKS; 4.1 Individual Actors; 4.2 Social Exchange Theory; 4.3 Social Forces; 4.3.1 Homophily; 4.3.2 Reciprocity; 4.3.3 Proximity; 4.3.4 Prestige; 4.3.5 Social Conformity; 4.3.6 Transitivity; 4.3.7 Balance; 4.4 Graph Structure; 4.4.1 Structural Balance; 4.4.2 Clusterability; 4.5 Agent Optimization Strategies in Networks; 4.5.1 Structural Holes; 4.5.2 Social Capital; 4.5.3 Link Optimization.
- 4.6 Hierarchy of Social Link Motivation4.7 Summary; Exercises; References; CHAPTER 5 SUBGROUP ANALYSIS; 5.1 Subgroups; 5.2 Organizational Theory; 5.3 Random Groups; 5.4 Heuristics for Subgroup Identification; 5.4.1 Attribute Defined; 5.4.2 Consecutive Correlation (CONCOR); 5.4.3 Newman-Girvan Grouping; 5.5 Analysis Methods; 5.5.1 Group Membership; 5.5.2 Hierarchical Clustering; 5.5.3 Block Model; 5.6 Summary; Chapter 5 Lab Exercise; Exercises; References; CHAPTER 6 DIFFUSION AND INFLUENCE; 6.1 Applications for Social Diffusion; 6.2 Strain Theory; 6.3 Social Context.
- 6.4 Group Impacts on Diffusion6.5 Network Structure and Diffusion; 6.6 Group Influence Strategies and Bases of Power; 6.7 Summary; Exercises; References; PART III DATA; CHAPTER 7 META-NETWORKS AND RELATIONAL ALGEBRA; 7.1 Modes of Data; 7.2 Source, Target, Direction; 7.3 Multimode Networks; 7.4 Bridging a Meta-Network; 7.5 Strength of Ties; 7.6 Summary; Chapter 7 Lab Exercise; Exercises; References; CHAPTER 8 SOURCES OF DATA; 8.1 Network Sampling; 8.2 Measuring Links; 8.3 Data Quality; 8.4 Additional Ethnographic Data Collection Methods; 8.5 Anonymity Issues; 8.6 Summary; Exercises; References.