The Plausibility of Personalizing Interfaces Using the Big Five Personality Traits

The research described in this paper reports the plausibility of personalizing interfaces based on the Big Five Personality Traits to create an enhanced user experience. Three datasets are used in this research: the ICS-BUE dataset, the AraPersonality dataset, and Open Psychometrics dataset. The data analysis consists of clustering the participants’ data and finding trait combinations. HDBScan and K-means methods are used to create clusters. The clusters produced did not have distinct dominant traits nor varying trait combinations. The results show that openness is the most dominant trait across all datasets, neuroticism is the least dominant trait across all datasets, and extraversion and conscientiousness alternate in dominance in the third and fourth positions. Accordingly, the predominant trait combinations are OACEN and OAECN. The AraPersonality dataset has agreeableness as the most dominant trait while the other two datasets have openness as the most dominant trait. The Open Psychometrics dataset has conscientiousness as the second dominant trait. Based on these findings, interface designers should not depend on a single dominant trait and should consider trait combinations. Accordingly, interface designs should cater to the predominant trait combination.