Qual Quant (2011) 45:985–987
DOI 10.1007/s11135-011-9483-4
Editorial: Applied and methodological issues
in the analysis of network data
Maria Rosaria D’Esposito · Susanna Zaccarin
Published online: 2 June 2011
© Springer Science+Business Media B.V. 2011
The Social network perspective has grown in popularity because it enables a very natural
approach to model relationships among interacting units. The relationships linking units may
be of many sorts: economic, political, interactional or affective to name just a few. Social
network analysis encompasses theories, methods and applications that are expressed in terms
of relational concepts or processes (Wasserman and Faust 1994; Scott 2000).
The large interest in social networks stems from the theoretical research questions and the
challenging methodological problems associated with the collection and analysis of social
network data. Conventional data focuses on units or actors and their attributes,network
data focus on actors and relations. This difference in emphasis motivates the choices that a
researcher has to make about research design, sampling strategies, measurement, and analysis
of resulting data. Progress in the statistical analysis of social networks has been impressive in
the last two decades, with increasing attention devoted to network modelling and to longitudi-
nal network dynamics (Snijders et al. 2006; Kolaczyk 2009; Krivitsky et al. 2009; Handcock
and Gile 2010; Snijders and Doreian 2010).
This special issue of Quality and Quantity comprises six papers, written by renowned
experts in the field from a number of countries. In each work, methodological and specific
application issues that may be involved in network analysis are discussed.
Three papers have been chosen from the ones presented at the international workshop
Social Network Analysis: Models and Methods for relational data (ARS09), held at the
University of Salerno, Italy on 13–14 July 2009. The focus of ARS 09 was on recent devel-
opments in the area of network analysis (networks visualization, dynamic networks, large net-
works, blockmodeling and statistical issues in modelling network data) and on applications in
M. R. D’Esposito (
B
)
Department of Economics and Statistics, University of Salerno, Fisciano, Italy
e-mail: mdesposito@unisa.it
S. Zaccarin
Department of Economics, Business, Mathematics and Statistics “B.de Finetti”,
University of Trieste, Trieste, Italy
e-mail: susanna.zaccarin@econ.units.it
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