Characterizing Hirability via Personality and Behavior
Harshit Malik, Hersh Dhillon, Roland Goecke, Ramanathan Subramanian

TL;DR
This study models job hirability as a personality trait using multimodal behavioral cues and demonstrates that a two-step prediction process from behavioral data to personality and then to hirability outperforms direct prediction, with multimodal cues enhancing accuracy.
Contribution
It introduces a novel approach of modeling hirability as a personality construct and evaluates multimodal behavioral cues for improved hirability prediction.
Findings
Two-step prediction process outperforms direct prediction.
Visual cues like eye and body movements are as effective as face cues.
Multimodal behavior influences personality impressions, e.g., cuss words affect Conscientiousness perception.
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 ~5000 FICS videos are as follows. (1) For each of the \emph{text}, \emph{audio} and \emph{visual}…
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Taxonomy
TopicsPersonality Traits and Psychology · Mental Health Research Topics
