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

Objective: Past applications of the lexical approach to type‐noun personality structures have yielded different results compared with those generated for adjectival personality structures, since then new methods have arisen for identifying robust higher‐dimensionality structure in data. This research aims to identify an optimal taxonomy of English language type‐nouns. Method: Current study reanalyzed 372 type‐nouns from a previous study emphasizing robustness across methodological variations (original vs. ipsatized data, oblique vs. orthogonal rotations, convergence between male and female target ratings) to determine a replicable but more comprehensive model of personality type‐noun structure. Results: A 13‐factor original‐data oblimin‐rotated solution was determined to be the most robust model, except for a one‐factor model that was far less comprehensive and informative; an original‐data 32‐factor oblimin‐rotated solution was also fairly robust. Although each of the Big Five adjectival markers indicated a large correlation with one or more type‐noun factors; nearly half of the 13 type‐noun factors lacked such large correlations with the Big Five. Conclusions: A high‐dimensionality approach thus indicated that type‐nouns capture substantial content beyond the Big Five. A comparison with the character‐types described by an ancient philosopher (Theophrastus) signified that some granular type‐noun dimensions may have stability across multiple millennia. [ABSTRACT FROM AUTHOR]