Suraj Bandyopadhyay, A. R. Rao, Bikas K. Sinha
Anteprima
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.
Key Features
•Reviews SNA concepts and basic parameters
•Includes a chapter devoted to graphs providing exploring many graph-theoretic features of SNA
•Longitudinal intra-village study of day to day helping and cooperating behaviors to demonstrate the analysis of network data using statistical applications
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
