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Multiple factor analysis for time-varying two-mode networks

Published online by Cambridge University Press:  12 February 2015

GIANCARLO RAGOZINI ,
DOMENICO DE STEFANO  and
MARIA ROSARIA D'ESPOSITO
GIANCARLO RAGOZINI
Affiliation:
Department of Political Science, University of Naples Federico II, Naples, Italy (e-mail: [email protected])
DOMENICO DE STEFANO
Affiliation:
Department of Political and Social Sciences DiSPeS, University of Trieste, Trieste, Italy (e-mail: [email protected])
MARIA ROSARIA D'ESPOSITO
Affiliation:
Department of Economics and Statistics, University of Salerno, Fisciano, Italy (e-mail: [email protected])
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Abstract

Most social networks present complex structures. They can be both multi-modal and multi-relational. In addition, each relationship can be observed across time occasions. Relational data observed in such conditions can be organized into multidimensional arrays and statistical methods from the theory of multiway data analysis may be exploited to reveal the underlying data structure. In this paper, we adopt an exploratory data analysis point of view, and we present a procedure based on multiple factor analysis and multiple correspondence analysis to deal with time-varying two-mode networks. This procedure allows us to create static displays in order to explore network evolutions and to visually analyze the degree of similarity of actor/event network profiles over time while preserving the different statuses of the two modes.

Keywords

multiple factor analysismultiple correspondence analysistwo-mode networkstime-varying networks
Type
Research Article
Information
Network Science , Volume 3 , Issue 1: Networks in Space and in Time: Methods and Applications , March 2015 , pp. 18 - 36
Copyright
Copyright © Cambridge University Press 2015 

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