TY - GEN
T1 - Examining the Influence of Personality and Multimodal Behavior on Hireability Impressions
AU - Malik, Harshit
AU - Dhillon, Hersh
AU - Parameshwara, Ravikiran
AU - Goecke, Roland
AU - Subramanian, Ramanathan
N1 - Publisher Copyright:
© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2023/12/15
Y1 - 2023/12/15
N2 - While personality traits have been traditionally modeled as behavioral constructs, we novelly posit \emph{job hireability} as a \emph{personality construct}. To this end, we examine correlates among personality and hireability measures on the \textit{First Impressions Candidate Screening} dataset. Modeling hireability as both a discrete and continuous variable, and the \emph{big-five} OCEAN personality traits as predictors, we utilize (a) multimodal behavioral cues, and (b) personality trait estimates obtained via these cues for hireability prediction (HP). For each of the \emph{text}, \emph{audio} and \emph{visual} modalities, HP via (b) is found to be more effective than (a). Also, superior results are achieved when hireability is modeled as a continuous rather than a categorical variable. Interestingly, eye and bodily visual cues perform comparably to facial cues for predicting personality and hireability. Explanatory analyses reveal that multimodal behaviors impact personality and hireability impressions: \textit{e.g.}, Conscientiousness impressions are impacted by the use of \textit{positive adjectives} (verbal behavior) and \emph{eye movements} (non-verbal behavior), confirming prior observations.
AB - While personality traits have been traditionally modeled as behavioral constructs, we novelly posit \emph{job hireability} as a \emph{personality construct}. To this end, we examine correlates among personality and hireability measures on the \textit{First Impressions Candidate Screening} dataset. Modeling hireability as both a discrete and continuous variable, and the \emph{big-five} OCEAN personality traits as predictors, we utilize (a) multimodal behavioral cues, and (b) personality trait estimates obtained via these cues for hireability prediction (HP). For each of the \emph{text}, \emph{audio} and \emph{visual} modalities, HP via (b) is found to be more effective than (a). Also, superior results are achieved when hireability is modeled as a continuous rather than a categorical variable. Interestingly, eye and bodily visual cues perform comparably to facial cues for predicting personality and hireability. Explanatory analyses reveal that multimodal behaviors impact personality and hireability impressions: \textit{e.g.}, Conscientiousness impressions are impacted by the use of \textit{positive adjectives} (verbal behavior) and \emph{eye movements} (non-verbal behavior), confirming prior observations.
KW - Hireability
KW - Personality traits
KW - Multimodal
KW - Behavioural cues
KW - Regression
KW - Classification
UR - https://www.iitrpr.ac.in/ICVGIP/
UR - http://www.scopus.com/inward/record.url?scp=85185840148&partnerID=8YFLogxK
U2 - 10.1145/3627631.3627658
DO - 10.1145/3627631.3627658
M3 - Conference contribution
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 9
BT - Proceedings of ICVGIP 2023 - 14th Indian Conference on Computer Vision, Graphics and Image Processing
A2 - Jawahar, CV
A2 - Natarajan, Vijay
A2 - Raman, Shanmuganathan
A2 - Balasuburamanian, Vineeth
PB - Association for Computing Machinery (ACM)
T2 - The Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP)
Y2 - 15 December 2023 through 17 January 2024
ER -