Full Description
Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze network data. Clearly demonstrates how graph-theoretic and statistical techniques can be employed to study some important parameters of global social networks. The authors uses real life village-level social networks to illustrate the practicalities, potentials, and constraints of social network analysis ("SNA"). They also offer relevant sampling and inferential aspects of the techniques while dealing with potentially large networks.
Intended Audience
This supplemental text is ideal for a variety of graduate and doctoral level courses in social network analysis in the social, behavioral, and health sciences
Contents
PREFACE
1. Introduction to Social Network Analysis
2. Introduction to Digraphs
3. Graph-Theoretic and Statistical Models
4. Validation of Statistical Models
5. Graph-theoretic and Statistical Measures and Methods
6. Graph-theoretic Case Studies
7. Sampling and Inference in a Social Network
