A new conception of personality based on network analysis has been recently proposed to overcome some of the limitations of the latent-variable theory of personality. While the latent-variable theory assumes that the covariation among the thoughts, feelings, and behaviors characterizing a personality domain can be explained by the effect of an unobservable latent variable (e.g., extraversion), the network approach conceives personality as emerging from direct interactions among these thoughts, feelings and behaviors. The network perspective motivates new ways of analyzing personality data and it can be especially important for investigating the mechanisms underlying personality. In this work, we present the basic network concepts and discuss several alternative ways to define networks from the data that are typically collected in personality psychology. The most important network indices, such as indices of centrality and of clustering coefficient, are described: we examine the properties of each index and explain why some of them, especially some indices of clustering coefficient, should not be applied to personality psychology data sets. Three new indices of clustering coefficient are proposed that are compatible with personality networks: their properties are tested both on simulated networks and networks based on actual personality psychology data. We present two applications of network analysis. The first application considers a network of 24 personality facets: we show how these facets relate to each other, and discuss both the local and the global properties of the network. The second application focuses on the dimension conscientiousness: We show that while some mechanisms underlying conscientiousness are common to many facets, other mechanisms may specifically characterize some facets and not others. By means of network analysis, we draw a comprehensive maps of conscientiousness that can serve as a guidance for future studies. The application of network analysis to the field of personality psychology is recent and its potentialities has not been fully explored yet: in the final part of this work, we discuss the limitations of our investigation and propose future developments of our research that can contribute to overcoming its limits.

(2015). Network analysis: a new perspective on personality psychology. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2015).

Network analysis: a new perspective on personality psychology

COSTANTINI, GIULIO
2015

Abstract

A new conception of personality based on network analysis has been recently proposed to overcome some of the limitations of the latent-variable theory of personality. While the latent-variable theory assumes that the covariation among the thoughts, feelings, and behaviors characterizing a personality domain can be explained by the effect of an unobservable latent variable (e.g., extraversion), the network approach conceives personality as emerging from direct interactions among these thoughts, feelings and behaviors. The network perspective motivates new ways of analyzing personality data and it can be especially important for investigating the mechanisms underlying personality. In this work, we present the basic network concepts and discuss several alternative ways to define networks from the data that are typically collected in personality psychology. The most important network indices, such as indices of centrality and of clustering coefficient, are described: we examine the properties of each index and explain why some of them, especially some indices of clustering coefficient, should not be applied to personality psychology data sets. Three new indices of clustering coefficient are proposed that are compatible with personality networks: their properties are tested both on simulated networks and networks based on actual personality psychology data. We present two applications of network analysis. The first application considers a network of 24 personality facets: we show how these facets relate to each other, and discuss both the local and the global properties of the network. The second application focuses on the dimension conscientiousness: We show that while some mechanisms underlying conscientiousness are common to many facets, other mechanisms may specifically characterize some facets and not others. By means of network analysis, we draw a comprehensive maps of conscientiousness that can serve as a guidance for future studies. The application of network analysis to the field of personality psychology is recent and its potentialities has not been fully explored yet: in the final part of this work, we discuss the limitations of our investigation and propose future developments of our research that can contribute to overcoming its limits.
PERUGINI, MARCO
personality psychology, network analysis, conscientiousness, clustering coefficients, HEXACO
M-PSI/03 - PSICOMETRIA
English
9-feb-2015
Scuola di Dottorato in Psicologia e Scienze Cognitive
PSICOLOGIA SPERIMENTALE, LINGUISTICA E NEUROSCIENZE COGNITIVE - 52R
26
2013/2014
open
(2015). Network analysis: a new perspective on personality psychology. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2015).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/75269
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