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Models for Social Networks With Statistical Applications
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Models for Social Networks With Statistical Applications

June 2010 | 256 pages | SAGE Publications, Inc
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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

 
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

Too advanced. May consider for a future advanced research methods course.

Dr Tirupalavanam Ganesh
School for Engineering of Matter, Transport and Energy, Arizona State University - Tempe
September 26, 2011
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This is a great text that I hope to use in a more advanced research methods class.

MICHELLE MAHON
Psychology , argosy univ
March 30, 2011
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I found this textbook to be good in terms of exposing the graph theoretic background required of this research domain but the book is lagging significantly in terms of application scope. There is a need to discuss a broader spectrum of applications of SNA.

Dr Christos Makrigeorgis
School Of Management, Walden University
March 8, 2011
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This book, while well written, is quite heavy on mathematical formulas and not suitable for this class. The book uses well thought out case studies and presents a unique perspective on social networks.

Mr Bob Snead
Educational Psychology Dept, University of Northern Colorado
October 1, 2010
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It is a wonderful comprehensive book, but far beyond the level of my students' statistical abilities, besides, the focus was different from what I expected. We focus more on interpretation of statistical analysis than designing at this level. Thanks for the opportunity to review it.

Dr Yoko Miura
Educational Leadership Dept, Wright State University
September 23, 2010
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Key features

Key Features

  • Reviews SNA concepts and basic parameters
  • Includes a chapter devoted to graphs, providing a basis for 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

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