The idea that individuals tend to choose a romantic partner following similarities on personality traits has always attracted much attention in the psychological literature, although results were controversial. We conducted a new data analysis approach to personality traits of 235 newlywed couples. Univariate analysis revealed that a neurotic husband is usually paired with a lesser extrovert and open wife. To figure out if this mating selection pattern may be translated in a mathematical predictive model a twofold approach was employed by using Partial Least Squares regression and machine learning algorithm. The experimental results demonstrate that marital assortment for personality is a multi-trait complementarity process but these data are unable to predict human mating.

May personality influence the selection of life-long mate? A multivariate predictive model

Cerasa A.;Martino I.;Sarica A.;
2020-01-01

Abstract

The idea that individuals tend to choose a romantic partner following similarities on personality traits has always attracted much attention in the psychological literature, although results were controversial. We conducted a new data analysis approach to personality traits of 235 newlywed couples. Univariate analysis revealed that a neurotic husband is usually paired with a lesser extrovert and open wife. To figure out if this mating selection pattern may be translated in a mathematical predictive model a twofold approach was employed by using Partial Least Squares regression and machine learning algorithm. The experimental results demonstrate that marital assortment for personality is a multi-trait complementarity process but these data are unable to predict human mating.
2020
Machine learning
Mate selection
Partial least squares regression
Personality prediction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12317/74832
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