Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Fausts Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or two-mode networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks. Contents
1. Introduction
2. Recent developments in network measurement
3. Network sampling and model fitting
4. Extending centrality
5. Positional analyses of sociometric data
6. Network models and methods for studying the diffusion of innovations
7. Using correspondence analysis for joint displays of affiliation networks
8. An introduction to random graphs, dependence graphs, and p*
9. Random graph models for social networks: multiple relations or multiple raters
10. Interdependencies and social processes: dependence graphs and generalized dependence structures
11. Models for longitudinal network data
12. Graphical techniques for exploring social network data
13. Software for social network analysis.

Author/Editor Details
Edited by: Peter J. Carrington, University of Waterloo, Ontario
Edited by: John Scott, University of Essex
Edited by: Stanley Wasserman, Indiana University, Bloomington