Book contents
- Frontmatter
- Contents
- Acknowledgments
- Contributors
- 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 Graphic Techniques for Exploring Social Network Data
- 13 Software for Social Network Analysis
- Index
- Structural Analysis in the Social Sciences
1 - Introduction
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Acknowledgments
- Contributors
- 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 Graphic Techniques for Exploring Social Network Data
- 13 Software for Social Network Analysis
- Index
- Structural Analysis in the Social Sciences
Summary
Interest in social network analysis has grown massively in recent years. This growth has been matched by an increasing sophistication in the technical tools available to users. Models and Methods in Social Network Analysis (MMSNA) presents the most important of those developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. It is a collection of original chapters by leading methodologists, commissioned by the three editors to review recent advances in their particular areas of network methods.
As is well-known, social network analysis has been used since the mid-1930s to advance research in the social and behavioral sciences, but progressed slowly and linearly, until the end of the century. Sociometry (sociograms, sociomatrices), graph theory, dyads, triads, subgroups, and blockmodels – reflecting substantive concerns such as reciprocity, structural balance, transitivity, clusterability, and structural equivalence – all made their appearances and were quickly adopted by the relatively small number of “network analysts.” It was easy to trace the evolution of network theories and ideas from professors to students, from one generation to the next. The field of network analysis was even analyzed as a network (see, for example, Mullins 1973, as well as analyses by Burt in 1978, and Hummon and Carley in 1993). Many users eventually became analysts, and some even methodologists. A conference of methodologists, held at Dartmouth College in the mid-1970s, consisted of about thirty researchers (see Holland and Leinhardt 1979) and really did constitute a “who's who” of the field – an auspicious, but rather small gathering.
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- Models and Methods in Social Network Analysis , pp. 1 - 7Publisher: Cambridge University PressPrint publication year: 2005
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