Constructing personality maps, mapping personality constructs: multidimensional scaling recovers the big five factors from internal and external structure.

This report examines the structure of similarities underlying the lexicon of personality-trait description, when "similarity" is defined and measured in terms of (a) semantic judgment and (b) covariance in actual use. A lexicon of 60 trait adjectives was examined, using several procedures for collecting semantic judgments. Similarity data of both kinds were analyzed with multidimensional scaling (MDS) to provide a parsimonious representation of underlying structure. The convergence between semantic judgments and covariance within trait-attribution data was substantial; both kinds of data evinced the same structure when collected for subsets of adjectives. Canonical correlation was employed to find the number of dimensions shared across MDS solutions. Interpretation of the results was facilitated by individual-differences MDS, which can select an optimal set of underlying dimensions, and at the same time accommodate the differences between data sets that arise when data-collection procedures differ in the relative emphasis they place upon those dimensions. We interpret the small number and shared nature of the dimensions by arguing that the lexicon's structure relates to trait perception rather than personality structure per se, even when probed with trait-attribution covariance.