High-dimensionality structure in English-language personality type-nouns.

Area of Science:

• Psychology
• Lexical studies
• Personality structure

Background:

• Previous lexical approaches to type-noun personality structures yielded varied results compared to adjectival structures.
• Advancements in data analysis methods enable more robust identification of higher-dimensionality structures.

Purpose of the Study:

• To identify an optimal taxonomy of English language type-nouns.
• To develop a more comprehensive and replicable model of personality type-noun structure.

Main Methods:

• Reanalysis of 372 type-nouns from a prior study.
• Emphasized robustness across methodological variations: original vs. ipsatized data, oblique vs. orthogonal rotations, and convergence between male and female ratings.

Main Results:

• A 13-factor solution using original data with oblimin rotation was the most robust model.
• Nearly half of the 13 type-noun factors showed limited correlation with the Big Five adjectival markers.
• A one-factor model was less informative, while a 32-factor solution was also robust.

Conclusions:

• High-dimensionality analysis indicates type-nouns capture significant content beyond the Big Five personality traits.
• Some granular type-noun dimensions show remarkable stability, with parallels to ancient philosophical character types.