Predicting Job-Hopping Motive of Candidates Using Answers to Open-ended Interview Questions
July 22, 2020 Β· Declared Dead Β· π Journal of Computational Social Science
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Authors
Madhura Jayaratne, Buddhi Jayatilleke
arXiv ID
2007.11189
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CL
Citations
5
Venue
Journal of Computational Social Science
Last Checked
4 months ago
Abstract
A significant proportion of voluntary employee turnover includes people who frequently move from job to job, known as job-hopping. Our work shows that language used in responding to interview questions on past behaviour and situational judgement is predictive of job-hopping motive as measured by the Job-Hopping Motives (JHM) Scale. The study is based on responses from over 45,000 job applicants who completed an online chat interview and self-rated themselves on JHM Scale. Five different methods of text representation were evaluated, namely four open-vocabulary approaches (TF-IDF, LDA, Glove word embeddings and Doc2Vec document embeddings) and one closed-vocabulary approach (LIWC). The Glove embeddings provided the best results with a correlation of r = 0.35 between sequences of words used and the JHM Scale. Further analysis also showed a correlation of r = 0.25 between language-based job-hopping motive and the personality trait Openness to experience and a correlation of r = -0.09 with the trait Agreeableness.
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