利用开放式面试答案预测求职者跳槽动机
Predicting Job-Hopping Motive of Candidates Using Answers to Open-ended Interview Questions
摘要：
员工自愿离职的很大一部分包括那些经常从一个工作换到另一个工作的人，即所谓的跳槽。我们的研究表明，在回答关于过去行为和情景判断的面试问题时使用的语言可以预测跳槽动机（JHM）量表。该研究基于超过45，000名求职者的回复，这些求职者完成了在线聊天面试并在JHM量表上进行了自我评价。五种不同的文本表示方法进行了评估，即四个开放的词汇方法（TF-IDF，LDA，手套词嵌入和Doc 2 Vec文档嵌入）和一个封闭的词汇方法（LIWC）。手套嵌入提供了最好的结果，使用的单词序列和JHM量表之间的相关性为r = 0.35。进一步的分析还发现，语言类跳槽动机与人格特质经验开放性之间的相关系数为r = 0.25，与人格特质工作能力之间的相关系数为r = -0.09。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
