Personality Traits in 12 Countries Defined by the ‘Big Five’ are Found to Have a Culture Dependency: Implications for Modeling Citizens’ Personalities

Abstract: This study critically evaluates the reliability and validity of the widely used Five Factor Model (FFM) or 'Big Five' personality traits framework across 12 Latin American countries. Conventional psychometric assessments based on factor analysis have significant methodological limitations when applied to categorical data. Addressing these concerns, we employed a Bayesian statistical approach utilizing Dirichlet and Beta distributions for categorical responses obtained from 5,175 participants who completed the IPIP-R questionnaire. Our novel methodology includes Monte Carlo simulations, confusion matrices, and probability density function estimations, effectively compensating for inherent sample size imbalances. Findings demonstrate substantial cultural variations in the distribution of personality traits, contradicting the presumed universality of the FFM. Additionally, notable differences were observed between male and female respondents, influenced by nationality. Furthermore, natural language processing techniques combined with the UMAP dimensionality reduction algorithm revealed that linguistic clustering of questionnaire items does not explain cultural differences. Our results demonstrate the inadequacy of factor analysis for analyzing categorical psychometric data, necessitating instead rigorous Bayesian methods. This study significantly impacts how personality assessments should be utilized in policymaking, corporate environments, and artificial intelligence applications, emphasizing the necessity of culturally sensitive and statistically robust approaches. The outcomes are discussed in relation to creation of citizen profiles and advanced personality modelling.

Keywords: Beta distribution, Dirichlet distribution, Big Five, Personality psychology, Confusion matrix

DOI: 10.54941/ahfe1006711

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