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In this book, leading methodologists address the issue of how effectively to apply the latest developments in social network analysis to behavioural and social science disciplines.

Topics examined include: ways to specify the network contents to be studied; how to select the method for representing network structures; how social network analysis has been used to study interorganizational relations via the resource dependence model; how to use a contact matrix for studying the spread of disease in epidemiology; and how cohesion and structural equivalence network theories relate to studying...

Social network analysis, which focuses on relationships among social entities, is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. As the first book to provide a comprehensive coverage of the methodology and applications of the field, this study is both a reference book and a textbook.

This volume is an important complement to Wasserman and Faust's Social Network Analysis: Methods and Applications (Cambridge, 1995). The authors, leading methodologists, present the most significant developments in quantitative models and methods for analyzing social network data that appeared in the 1990s. They review recent advances in network measurement, network sampling, analysis of centrality, positional analysis or blockmodelling, analysis of diffusion through networks, analysis of affiliation or "two-mode" networks, the theory of random graphs, and dependence graphs.

This volume is an important complement to Wasserman and Faust's Social Network Analysis: Methods and Applications (Cambridge, 1995). The authors, leading methodologists, present the most significant developments in quantitative models and methods for analyzing social network data that appeared in the 1990s. They review recent advances in network measurement, network sampling, analysis of centrality, positional analysis or blockmodelling, analysis of diffusion through networks, analysis of affiliation or "two-mode" networks, the theory of random graphs, and dependence graphs.