Date
2012-06
Indexation documentaire
Sociologie économique
Subject
Relations humaines; Analyse de réseau; Sociologie des organisations; Modèles mathématiques; Réseaux sociaux
Titre du colloque
Multilevel Social Networks Symposium
Date du colloque
06-2012
Ville du colloque
Manchester
Pays du colloque
Royaume-Uni
Auteur
Wang, Peng
Snijders, Tom
Robins, Garry
Lomi, Alessandro
Koskinen, Johan
Lazega, Emmanuel
Type
Communication / Conférence
Résumé en anglais
We know that settings are important when modeling networks (Feld, 1981;
Pattison & Robins, 2002; Preciado and Snijders, 2011) and that network
endogeneities may play out subtly differently in different contexts (for example
Lubbers and Sniders, 2007), yet much of sna is concerned with explaining the
structure of particular networks. There are obvious reasons why this should be.
Firstly computational limitations of currently available best methods for analysis
require that networks are of manageable sizes. Secondly, there are a host of
issues surrounding drawing the boundary of a network and this is most easily
done by delineating the networks node set according to some common affiliation,
setting or context. Thirdly, there has up until recently been no apparent way of
taking heteregonenity across settings into account. Fourth, the approaches that
conceptually have been available for handling heterogeneity across contexts,
models for multilevel analysis of networks (MAN), are not well suited for
handling partially overlapping settings nor are they well equipped to detail the
kind of dependencies that stem from multiple and overlapping affiliations. With
the advent of the multilevel network ERGM (MLNERGM) (Wang et al., 2012;
Wasserman and Iacobucci, 1991) we now have a tool for encompassing all of
these issues as well as having at our disposal the additional benefit of being
able to properly specify relational dependencies between settings. We conceive
of multilevel network analysis (MNA) as being analyses for data where we have
a people set P and an affiliation set A, with ties in PxP, PxA, AxP, and AxA. The
purpose of this paper is to seek to provide a consistent framework for MAN in
terms of MNA, and to illustrate the limitations of the former. We illustrate several
aspects of how hierarchical ERGMs for MAN relates to MNA by way of
empirically informed Monte Carlo studies as well as a brief empirical
analysis. Most researchers also associate the term “multilevel” in a network
context with MAN and, in light of computation issues, MAN might appear an
appealing technique for taking heterogeneity into account.