Characteristic Characteristics

• Main Authors: Brocklebank, Sean, Pauls, Scott, Rockmore, Daniel, Bates, Timothy C
• Format: Journal Article
• Language: English
• Published: 06.07.2011
• Subjects: Computer Science - Information Retrieval; Physics - Data Analysis, Statistics and Probability; Statistics - Applications
• DOI: 10.48550/arxiv.1107.1229

While five-factor models of personality are widespread, there is still not universal agreement on this as a structural framework. Part of the reason for the lingering debate is its dependence on factor analysis. In particular, derivation or refutation of the model via other statistical means is a worthwhile project. In this paper we use the methodology of spectral clustering to articulate the structure in the dataset of responses of 20,993 subjects on a 300-item item version of the IPIP NEO personality questionnaire, and we compare our results to those obtained from a factor analytic solution. We found support for five- and six-cluster solutions. The five-cluster solution was similar to a conventional five-factor solution, but the six-cluster and six-factor solutions differed significantly, and only the six-cluster solution was readily interpretable: it gave a model similar to the HEXACO model. We suggest that spectral clustering provides a robust alternative view of personality data.