Detecting Deceptive Impression Management Behaviors in Interviews Using Natural Language Processing
Deceptive impression management (IM) is often used by applicants in employment interviews to improve their chances of receiving a job offer. Self-report measures of deceptive IM are typically used to evaluate interview faking in a lab setting but are limited when used in practice due to social desirability concerns. Given this limitation, natural language processing (NLP) has potential as a tool to unobtrusively assess raw interview content and measure deceptive IM. This study examined the use of open and closed-vocabulary NLP approaches for the detection of deceptive IM in mock employment interviews. In general, neither of these approaches successfully predicted deceptive IM. Several possible conclusions based on these findings are discussed. However, given the lack of empirical support for this method, organizations should proceed with caution when deciding to use NLP techniques to predict deceptive IM in employment interviews.
Deceptive impression management, Employee interviews, Interview faking behaviors, LDA, LIWC, Natural language processing, Industrial and Organizational Psychology
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