Over the past few decades Social Network Analysis has found increasing application in many social research areas to describe relational ties among social entities. In this paper, we propose to use Multidimensional Data Analysis in the framework of SNA in order to explore the structural properties of a network. In particular, we refer to Contiguity Analysis in order to deal with relational data defined by ties among the actors and described by network centrality and clustering coefficients. The expected results consist of the definition of a network meta-analysis able to synthesise and visualise the pattern of social relationships in a metric space where the related data structure is described. The proposed method is applied to an illustrative example in the context of a virtual learning community.

Factorial Contiguity Maps to Explore Relational Data Patterns

GIORDANO, Giuseppe;VITALE, MARIA PROSPERINA
2007

Abstract

Over the past few decades Social Network Analysis has found increasing application in many social research areas to describe relational ties among social entities. In this paper, we propose to use Multidimensional Data Analysis in the framework of SNA in order to explore the structural properties of a network. In particular, we refer to Contiguity Analysis in order to deal with relational data defined by ties among the actors and described by network centrality and clustering coefficients. The expected results consist of the definition of a network meta-analysis able to synthesise and visualise the pattern of social relationships in a metric space where the related data structure is described. The proposed method is applied to an illustrative example in the context of a virtual learning community.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/2501420
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