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Predicting job-hopping motive of candidates using answers to open-ended interview questions

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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Notes

  1. https://www.predictivehire.com/.

  2. https://radimrehurek.com/gensim/.

  3. https://spacy.io/.

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Correspondence to Madhura Jayaratne.

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Both authors are employed at PredictiveHire, the creator of the FirstInterview product that was used to collect the data for the research.

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Jayaratne, M., Jayatilleke, B. Predicting job-hopping motive of candidates using answers to open-ended interview questions. J Comput Soc Sc 5, 611–628 (2022). https://doi.org/10.1007/s42001-021-00138-4

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  • DOI: https://doi.org/10.1007/s42001-021-00138-4

Keywords

  • Job-hopping
  • Turnover
  • Structured interviews
  • Natural language processing
  • Computational linguistic analysis
  • Machine learning
  • HEXACO personality model