Network analysis has just recently started to be applied to the study of personality, providing both a new theoretical perspective and a new set of analytical tools to investigate the structural and dynamic properties of personality. We present the fundamental concepts of network analysis and review recent studies that have applied the network methodology in personality psychology, with important implications for how personality can be conceptualized as well as measured. Several methods can be used to define networks from the data that are typically collected in personality psychology studies. We review such methods and discuss indices that help to summarize important properties of the networks obtained. We will focus especially on centrality indices, which allow us to identify elements of the network that are particularly important, and on indices of clustering coefficients, that allow the identification of elements that are locally redundant and therefore less essential for the network to operate. The concepts are presented from a theoretical point of view and illustrated by applying them on personality data-sets.
Costantini, G., Perugini, M. (2016). Network Analysis: A New Way to Think about Personality. In U. Kumar (a cura di), The Wiley Handbook of Personality Assessment (pp. 74-89). New York : Wiley Blackwell [10.1002/9781119173489.ch6].
Network Analysis: A New Way to Think about Personality
COSTANTINI, GIULIO
;PERUGINI, MARCO
2016
Abstract
Network analysis has just recently started to be applied to the study of personality, providing both a new theoretical perspective and a new set of analytical tools to investigate the structural and dynamic properties of personality. We present the fundamental concepts of network analysis and review recent studies that have applied the network methodology in personality psychology, with important implications for how personality can be conceptualized as well as measured. Several methods can be used to define networks from the data that are typically collected in personality psychology studies. We review such methods and discuss indices that help to summarize important properties of the networks obtained. We will focus especially on centrality indices, which allow us to identify elements of the network that are particularly important, and on indices of clustering coefficients, that allow the identification of elements that are locally redundant and therefore less essential for the network to operate. The concepts are presented from a theoretical point of view and illustrated by applying them on personality data-sets.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.