Validation of Two Short Personality Inventories Using Self-Descriptions in Natural Language and Quantitative Semantics Test Theory.

ABSTRACT:

Background

If individual differences are relevant and prominent features of personality, then they are expected to be encoded in natural language, thus manifesting themselves in single words. Recently, the quantification of text data using advanced natural language processing techniques offers innovative opportunities to map people's own words and narratives to their responses to self-reports. Here, we demonstrate the usefulness of self-descriptions in natural language and what we tentatively call Quantitative Semantic Test Theory (QuSTT) to validate two short inventories that measure character traits.

Method

In Study 1, participants (N ₁ = 997) responded to the Short Character Inventory, which measures self-directedness, cooperativeness, and self-transcend

SUBMITTER: Garcia D 

PROVIDER: S-EPMC7043268 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature