Bayesian Network modeling for Dark Triad, aggression, and empathy

要旨

This study aimed to construct a Conditional Gaussian Bayesian Network (BN) model for Dark Triad, aggression, and empathy and to examine the validity of the constructed models as predictable. First, this study conducted a web questionnaire survey using the Short Dark Triad, Buss-Perry Aggression Questionnaire, and Multidimensional Empathy Scale. The BN models were automatically constructed obtained from 637 Japanese participants (372 males, 265 females, age range 22–69 years, M = 50.4, SD = 11.6). The model revealed that (1) psychopathy had a direct and positive arc on aggression types (physical aggression, hostility, and anger) and was negatively linked to other-oriented emotional reactivity and perspective-taking among empathy; (2) narcissism negatively predicted hostility and had a direct positive association with verbal aggression; and (3) Machiavellianism indirectly associated with aggression. Furthermore, the leave-one-out cross-validation (LOOCV) simulation revealed that the performance metrics (accuracy, recall, precision, and F1 score) for predicting the three Dark Triad traits of the test set were approximately 60 % to 70 % (chance level 50 % for High/Low). The precision reached a maximum of 80.4 %. This study revealed that BNs are a powerful and useful tool through automatic data-driven exploration of relationships between the Dark Triad and other personality traits. • Bayesian Network modeling for Dark Triad, aggression, and empathy • Psychopathy was linked positively and negatively to aggression and empathy, respectively. • Narcissism negatively predicted hostility but positively predicted verbal aggression. • Machiavellianism suggested an indirect relationship with aggression (anger and hostility).

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