Exploratory Social Network Analysis With Pajek

An extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software and data sets are available so readers can learn network analysis through application and case studies. Readers will have the knowledge, skill and tools to apply social network analysis across the social sciences, from anthropology and sociology to business administration and history. This second edition has a new chapter on random network models, for example, scale-free and small-world networks and Monte Carlo simulation; discussion of multiple relations, islands and matrix multiplication; new structural indices such as eigenvector centrality, degree distribution and clustering coefficients; new visualization options that include circular layout for partitions and drawing a network geographically as a 3D surface; and using Unicode labels.

Wouter de Nooy is Associate Professor in the Department of Communication Science at the University of Amsterdam, The Netherlands, and a member of the Amsterdam School of Communication Research (ASCoR) and the Netherlands School of Communication Research (NESCoR). Andrej Mrvar is Associate Professor of Social Science Informatics on the Faculty of Social Sciences, University of Ljubljana, Slovenia. He won several awards for graph drawings at competitions between 1995 and 2005. He has edited Metodoloski zvezki - Advances in Methodology and Statistics since 2000. Vladimir Batagelj is Professor of Discrete and Computational Mathematics at the University of Ljubljana, Slovenia, and a member of the editorial boards of Informatica and Journal of Social Structure. He has authored several articles in Communications of the ACM, Psychometrika, Journal of Classification, Social Networks, Discrete Mathematics, Algorithmica, Journal of Mathematical Sociology, Quality and Quantity, Informatica, Lecture Notes in Computer Science, Studies in Classification, Data Analysis, and Knowledge Organization.