English

Characterizing Hirability via Personality and Behavior

Computer Vision and Pattern Recognition 2020-06-23 v1

Abstract

While personality traits have been extensively modeled as behavioral constructs, we model \textbf{\textit{job hirability}} as a \emph{personality construct}. On the {\emph{First Impressions Candidate Screening}} (FICS) dataset, we examine relationships among personality and hirability measures. Modeling hirability as a discrete/continuous variable with the \emph{big-five} personality traits as predictors, we utilize (a) apparent personality annotations, and (b) personality estimates obtained via audio, visual and textual cues for hirability prediction (HP). We also examine the efficacy of a two-step HP process involving (1) personality estimation from multimodal behavioral cues, followed by (2) HP from personality estimates. Interesting results from experiments performed on \approx~5000 FICS videos are as follows. (1) For each of the \emph{text}, \emph{audio} and \emph{visual} modalities, HP via the above two-step process is more effective than directly predicting from behavioral cues. Superior results are achieved when hirability is modeled as a continuous vis-\'a-vis categorical variable. (2) Among visual cues, eye and bodily information achieve performance comparable to face cues for predicting personality and hirability. (3) Explanatory analyses reveal the impact of multimodal behavior on personality impressions; \eg, Conscientiousness impressions are impacted by the use of \emph{cuss words} (verbal behavior), and \emph{eye movements} (non-verbal behavior), confirming prior observations.

Cite

@article{arxiv.2006.12041,
  title  = {Characterizing Hirability via Personality and Behavior},
  author = {Harshit Malik and Hersh Dhillon and Roland Goecke and Ramanathan Subramanian},
  journal= {arXiv preprint arXiv:2006.12041},
  year   = {2020}
}

Comments

9 pages

R2 v1 2026-06-23T16:30:32.196Z