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A Comparison of χ 2 Metrics for the Assessment of Relational Similarities in Affiliation Networks

Authors :
Maria Rosaria D'Esposito
Giancarlo Ragozini
Domenico De Stefano
D. Vicari, A. Okada, G. Ragozini, C. Weihs
D'Esposito, M. R.
De Stefano, D.
Ragozini, Giancarlo
Donatella Vicari, Akinori Okada, Giancarlo Ragozini, Claus Weihs
D’Esposito, Maria Rosaria
DE STEFANO, Domenico
Source :
Studies in Classification, Data Analysis, and Knowledge Organization ISBN: 9783319066912
Publication Year :
2014
Publisher :
Springer International Publishing, 2014.

Abstract

Factorial techniques are widely used in Social Network Analysis to analyze and visualize networks. When the purpose is to represent the relational similarities, simple correspondence analysis is the most frequent used technique. However, in the case of affiliation networks, its use can be criticized because the involved χ 2 distance does not adequately reflect the actual relational patterns. In this paper we perform a simulation study to compare the metric involved in Correspondence Analysis with respect to the one in Multiple Correspondence Analysis. Analytical results and simulation outcomes show that Multiple Correspondence Analysis allows a proper graphical appraisal of the underlying two-mode relational structure.

Details

Language :
English
ISBN :
978-3-319-06691-2
ISBNs :
9783319066912
Database :
OpenAIRE
Journal :
Studies in Classification, Data Analysis, and Knowledge Organization ISBN: 9783319066912
Accession number :
edsair.doi.dedup.....1114b10e10468ce65200da67a245da91