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 Faust’s Social Network Analysis: Methods and Applications, it is a collection of original articles by leading methodologists reviewing recent advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodeling, 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, graphic techniques for exploring network data, and software for the analysis of social networks.

Peter J. Carrington is Professor of Sociology at the University of Waterloo and Editor of the Canadian Journal of Criminology and Criminal Justice. His main teaching and research interests are in the criminal and juvenile justice systems, social networks, and research methods and statistics. He has published articles in the Canadian Journal of Criminology and Criminal Justice, American Journal of Psychiatry, Journal of Mathematical Sociology, and Social Networks. He is currently doing research on police discretion, criminal and delinquent careers and networks, and the impact of the Youth Criminal Justice Act on the youth justice system in Canada.

John Scott is Professor of Sociology at the University of Essex. An active member of the British Sociological Association, he served as its president from 2001 until 2003. He has written more than fifteen books, including Corporate Business and Capitalist Classes (1997), Social Network Analysis (1991 and 2000), Sociological Theory (1995), and Power (2001). With James Fulcher, he is the author of the leading introductory textbook Sociology (1999 and 2003). He is a member of the Editorial Board of the British Journal of Sociology and is an Academician of the Academy of Learned Societies in the Social Sciences.

Stanley Wasserman is Rudy Professor of Sociology, Psychology, and Statistics at Indiana University. He has done research on methodology for social networks for thirty years. He has co-authored with Katherine Faust Social Network Analysis: Methods and Applications, published in 1994 in this series by Cambridge University Press, and has co-edited with Joseph Galaskiewicz Social Network Analysis: Research in the Social and Behavioral Sciences (1994). His work is recognized by statisticians, as well as social and behavioral scientists, worldwide. He is currently Book Review Editor of Chance and an Associate Editor of the Journal of the American Statistical Association and Psychometrika. He has also been a very active consultant and is currently Chief Scientist of Visible Path, an organizational network software firm.

Structural Analysis in the Social Sciences 27

Mark Granovetter, General editor

The series Structural Analysis in the Social Sciences presents approaches that explain social behavior and institutions by reference to relations among such concrete entities as persons and organizations. This contrasts with at least four other popular strategies: (a) reductionist attempts to explain by a focus on individuals alone; (b) explanations stressing the causal primacy of such abstract concepts as ideas, values, mental harmonies, and cognitive maps (thus, “structuralism” on the Continent should be distinguished from structural analysis in the present sense); (c) technological and material determination; and (d) explanation using “variables” as the main analytic concepts (as in the “structural equation” models that dominated much of the sociology of the 1970s), where structure is that connecting variables rather that actual social entities.

   The social network approach is an important example of the strategy of structural analysis; the series also draws on social science theory and research that is not framed explicitly in network terms, but stresses the importance of relations rather than the atomization of reduction or the determination of ideas, technology, or material conditions. Although the structural perspective has become extremely popular and influential in all the social sciences, it does not have a coherent identity, and no series yet pulls together such work under a single rubric. By bringing the achievements of structurally oriented scholars to a wider public, this series hopes to encourage the use of this very fruitful approach.

Other books in the series:

1. Mark S. Mizruchi and Michael Schwartz, eds., Intercorporate Relations: The Structural Analysis of Business
2. Barry Wellman and S. D. Berkowitz, eds., Social Structures: A Network Approach
3. Ronald L. Brieger, ed., Social Mobility and Social Structure
4. David Knoke, Political Networks: The Structural Perspective
5. John L. Campbell, J. Rogers Hollingsworth, and Leon N. Lindberg, eds., Governance of the American Economy
6. Kyriakos Kontopoulos, The Logics of Social Structure
7. Philippa Pattison, Algebraic Models for Social Structure
8. Stanley Wasserman and Katherine Faust, Social Network Analysis: Methods and Applications
9. Gary Herrigel, Industrial Constructions: The Sources of German Industrial Power
10. Philippe Bourgois, In Search of Respect: Selling Crack in El Barrio
11. Per Hage and Frank Harary, Island Networks: Communication, Kinship, and Classification Structures in Oceana
12. Thomas Schweizer and Douglas R. White, eds., Kinship, Networks, and Exchange
13. Noah E. Friedkin, A Structural Theory of Social Influence
14. David Wank, Commodifying Communism: Business, Trust, and Politics in a Chinese City
15. Rebecca Adams and Graham Allan, Placing Friendship in Context
16. Robert L. Nelson and William P. Bridges, Legalizing Gender Inequality: Courts, Markets and Unequal Pay for Women in America

Models and Methods in Social
Network Analysis

Edited by

PETER J. CARRINGTON
University of Waterloo

JOHN SCOTT
University of Essex

STANLEY WASSERMAN
Indiana University

CAMBRIDGE UNIVERSITY PRESS
Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo

Cambridge University Press
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www.cambridge.org
Information on this: www.cambridge.org/9780521809597

© Cambridge University Press 2005

This book is in copyright. Subject to statutory exception
and to the provisions of relevant collective licensing agreements,
no reproduction of any part may take place without
the written permission of Cambridge University Press.

First published 2005

Printed in the United States of America

A catalog record for this book is available from the British Library.

Library of Congress Cataloguing in Publication Data

Models and methods in social network analysis / edited by Peter J. Carrington, John Scott,
and Stanley Wasserman.
p. cm. – (Structural analysis in the social sciences)
Includes bibliographical references and index.
ISBN 0-521-80959-2 – ISBN 0-521-60097-9 (pb.)
1. Social networks – Mathematical models. 2. Social networks – Research – Methodology.
I. Carrington, Peter J., 1946– II. Scott, John, III. Wasserman, Stanley. IV. Series.
HM741.M63   2005
302.3 – dc22         2004051888

ISBN-13 978-0-521-80959-7 hardback
ISBN-10 0-521-80959-2 hardback

ISBN-13 978-0-521-60097-2 paperback
ISBN-10 0-521-60097-9 paperback

Cambridge University Press has no responsibility for
the persistence or accuracy of URLs for external or
third-party Internet Web sites referred to in this book
and does not guarantee that any content on such
Web sites is, or will remain, accurate or appropriate.

Contents

Acknowledgments

The editors want to thank Mary Child and Ed Parsons of Cambridge University Press and Mark Granovetter, the general editor of the series, for their support and patience during the long genesis of this volume. We are also grateful to Anthony Matarazzo, who prepared the index, and who created and maintained the Web site that served as a virtual workplace and meeting place for everyone who contributed to the book.

   We are, of course, very grateful to our contributors. Their expertise and hard work have made this an easy project for us. Thanks go to all of them.

   Preparation of the book was supported by Social Sciences and Humanities Research Council of Canada Standard Research Grants No. 410-2000-0361 and 410-2004-2136 and U.S. Office of Naval Research Grant No. N00014-02-1-0877.

   We dedicate this volume to social network analysts everywhere, in the hope that they will find these chapters useful in their research.

Contributors

Vladimir Batagelj is a professor of discrete and computational mathematics at the University of Ljubljana and is chair of the Department of Theoretical Computer Science at IMFM, Ljubljana. He is a member of the editorial boards of Informatica and the Journal of Social Structure. He was visiting professor at the University of Pittsburgh in 1990/1991 and at University of Konstanz (Germany) in 2002. His main research interests are in graph theory, algorithms on graphs and networks, combinatorial optimization, data analysis, and applications of information technology in education. He is co-author (with Andrej Mrvar) of Pajek, a program for analysis and visualization of large networks.

Steve P. Borgatti is Associate Professor of Organization Studies at Boston College. His research interests include social networks, cultural domain analysis, and organizational learning. He is co-author of the UCINET software package and a past President of INSNA, the professional association for social network researchers.

Peter J. Carrington is Professor of Sociology at the University of Waterloo and Editor of the Canadian Journal of Criminology and Criminal Justice. His main teaching and research interests are in the criminal and juvenile justice systems, social networks, and research methods and statistics. He has published articles in the Canadian Journal of Criminology and Criminal Justice, American Journal of Psychiatry, Journal of Mathematical Sociology, and Social Networks. He is currently doing research on police discretion, criminal and delinquent careers and networks, and the impact of the Youth Criminal Justice Act on the youth justice system in Canada.

Patrick Doreian is a professor of sociology and statistics at the University of Pittsburgh, where he also chairs the Department of Sociology. He edits the Journal of Mathematical Sociology and is a member of the editorial board of Social Networks. His research and teaching interests include social networks, social movements, and mathematical sociology.

Marijtje A. J. van Duijn is an assistant professor in the Department of Sociology of the University of Groningen. Her research interests are in applied statistics and statistical methods for discrete and/or longitudinal data, including multilevel modeling and social network analysis. She teaches courses on multivariate statistical methods and on item response theory.

Martin Everett has a masters degree in mathematics and a doctorate in social networks from Oxford University. He has been active in social network research for more than 25 years. During a sabbatical at the University of California, Irvine, in 1987, he teamed up with Stephen Borgatti, and they have collaborated ever since. Currently he is a Provost at the University of Westminster, London.

Katherine Faust is Associate Professor in the Sociology Department at the University of California, Irvine, and is affiliated with the Institute for Mathematical Behavioral Sciences at UCI. She is co-author (with Stanley Wasserman) of Social Network Analysis: Methods and Applications and numerous articles on social network analysis. Her current research focuses on methods for comparing global structural properties among diverse social networks; the relationship between social networks and demographic processes; and spatial aspects of social networks.

Anuška Ferligoj is a professor of statistics at the University of Ljubljana and is dean of the Faculty of Social Sciences. She has been editor of the series Metodoloski zvezki since 1987 and is a member of the editorial boards of the Journal of Mathematical Sociology, the Journal of Classification, Social Networks, and Statistics in Transition. She was a Fulbright Scholar in 1990 and Visiting Professor at the University of Pittsburgh. She was awarded the title of Ambassador of Science of the Republic of Slovenia in 1997. Her interests include multivariate analysis (constrained and multicriteria clustering), social networks (measurement quality and blockmodeling), and survey methodology (reliability and validity of measurement).

Ove Frank was professor of statistics at Lund University, Sweden, 1974–1984, and at Stockholm University from 1984, where he recently became emeritus. He is one of the pioneers in network sampling and has published papers on network methodology, snowball sampling, Markov graphs, clustering, and information theory. Jointly with David Strauss he introduced Markov graphs in 1986 and explained how sufficient network statistics can be deduced from explicit assumptions about the dependencies in a network.

Linton C. Freeman is a research professor in the Department of Sociology and in the Institute for Mathematical Behavioral Sciences at the University of California, Irvine. He began working in social network analysis in 1958 when he directed a structural study of community decision making in Syracuse New York. Freeman was an early computer user and taught information and/or computer science at Syracuse and at the universities of Hawaii and Pittsburgh. In 1978 he founded the journal Social Networks. Beginning in the 1950s, and continuing to the present time, one of his continuing areas of interest has been the graphical display of network structure.

Mark Huisman is an assistant professor in the Department of Psychology of the University of Groningen. He teaches courses on statistics and multivariate statistical methods. His current research interests focus on statistical modeling of social networks, methods for nonresponse and missing data, and software for statistical data analysis.

Laura M. Koehly is an assistant professor in the Department of Psychology at Texas A&M University. She completed her Ph.D. in quantitative psychology at the University of Illinois–Urbana/Champaign, after which she completed postdoctoral training at the University of Texas M.D. Anderson Cancer Center. Her methodological research interests focus on the development of stochastic models for three-way social network data and ego-centered network data. Her substantive research focuses on the application of social network methods in the health domain, specifically in the areas of hereditary cancers. She has recently developed a research program in organizational psychology that focuses on socialization processes within organizational settings, consensus and accuracy in perceptions of social structure, and the evolution of leadership within teams.

Peter V. Marsden is Professor of Sociology at Harvard University. His academic interests include social organization, social networks, and social science methodology. With James A. Davis and Tom W. Smith, Marsden is a co-Principal Investigator of the General Social Survey and has been a lead investigator for three National Organizations Studies conducted between 1991 and 2003.

Philippa Pattison is a professor in the Department of Psychology at the University of Melbourne. Her current research is focused on the development of dynamic network-based models for social processes and on applications of these models to a diverse range of phenomena, including mental health, organizational design, the emergence of markets, and disease transmission.

Garry Robins teaches quantitative methods in the Department of Psychology at the University of Melbourne, Australia. His research is centered on methodologies for social network analysis, particularly on exponential random graph (p^*) models. He has a wide range of collaborations arising from empirical research related to social networks.

John Scott is Professor of Sociology at the University of Essex. An active member of the British Sociological Association, he served as its president from 2001 until 2003. He has written more than fifteen books, including Corporate Business and Capitalist Classes (1997), Social Network Analysis (1991 and 2000), Sociological Theory (1995), and Power (2001). With James Fulcher, he is the author of the leading introductory textbook Sociology (1999 and 2003). He is a member of the Editorial Board of the British Journal of Sociology and is an Academician of the Academy of Learned Societies in the Social Sciences

Tom A. B. Snijders is professor of Methodology and Statistics in the Department of Sociology of the University of Groningen, The Netherlands, and Scientific Director of the Research and Graduate School ICS (Interuniversity Center for Social Science Theory and Methodology). His main research interests are social network analysis and multilevel analysis.

Thomas W. Valente is an associate professor in the Department of Preventive Medicine, Keck School of Medicine, and Director of the Master of Public Health Program at the University of Southern California. He is author of Evaluating Health Promotion Programs (2002, Oxford University Press); Network Models of the Diffusion of Innovations (1995, Hampton Press); and numerous articles on social network analysis, health communication, and mathematical models of the diffusion of innovations.

Stanley Wasserman is Rudy Professor of Sociology, Psychology, and Statistics at Indiana University. He has done research on methodology for social networks for 30 years. He has co-authored with Katherine Faust Social Network Analysis: Methods and Applications, published in 1994 in this series by Cambridge University Press, and has co-edited with Joseph Galaskiewicz Social Network Analysis: Research in Social and Behavioral Sciences (1994). He has also been a very active consultant and is currently Chief Scientist of Visible Path, an organizational network research firm.