Revisiting the IPIP-NEO Personality Hierarchy with Taxonomic Graph Analysis

Describing and understanding personality structure is fundamental to predict and explainhuman behavior. Recent research calls for large personality item pools to be analyzed fromthe bottom-up, as item-level analysis may reveal meaningful differences often obscured byaggregation. This study introduces and applies Taxonomic Graph Analysis (TGA), a comprehensivenetwork psychometrics framework aimed at identifying hierarchical structuresin personality from the bottom-up, to an open-source 300-item IPIP-NEO dataset (N =149,337). This framework addresses key methodological challenges that have hindered accuraterecovery of hierarchical structures, including local independence violations, wordingeffects, dimensionality assessment, and structural robustness. TGA revealed a three-levelstructure composed of 28 first-level dimensions (facets), 6 second-level dimensions (traits),and 3 third-level dimensions (meta-traits). Although some dimensions aligned with the theoreticalIPIP-NEO structure, there were considerable deviations including the emergenceof Sociability, Integrity, and Impulsivity traits at the second-level and a novel Disinhibitionmeta-trait at the third-level. The overarching theme of our findings was a hierarchical structurethat integrated empirical and theoretical findings that have been scattered across thepersonality literature, demonstrating TGA’s value to investigate hierarchical psychologicalconstructs. This study contributes to discussions on personality taxonomy by providing arigorous, data-driven perspective on the IPIP-NEO’s hierarchical structure.