  Fundamental Big Five personality traits (e.g., Extraversion) and their facets
(e.g., Activity) are known to correlate with a broad range of linguistic
features and, accordingly, the recognition of personality traits from text is a
well-known Natural Language Processing task. Labelling text data with facets
information, however, may require the use of lengthy personality inventories,
and perhaps for that reason existing computational models of this kind are
usually limited to the recognition of the fundamental traits. Based on these
observations, this paper investigates the issue of personality facets
recognition from text labelled only with information available from a shorter
personality inventory. In doing so, we provide a low-cost model for the
recognition of certain personality facets, and present reference results for
further studies in this field.
