Who Are You Meant to Be? Predicting Psychological Indicators and Occupations based on Personality Traits

Abstract

Recognition of psychological characteristics based on massive data and computer machine learning algorithms has gradually become a new way for psychological research. As we all know, person-job fit is an important consideration in recruitment and selection. Most existing selection process can reliably measure skills fit, i.e., matching job seekers’ skills/work experience with job demand. What is often harder to assess is the compatibility between job seekers’ motivational needs/career aspirations and job characteristics, which will ultimately determine their career progress and job satisfaction. With the increasing application of machine learning methods in psychology, this paper constructed classification models to predict individuals’ needs, career aspiration, and occupation through their personality traits. This enables automatic access to individuals’ psychological indicators, with the MLP (Multi-Layer Perceptron) method showing the highest prediction accuracy. In addition, it conducted a comparative analysis of the distribution of personality characteristics in different occupations. Based on the study results, we put forward some countermeasures and suggestions for application in human resource management.

Keywords

Personality traits / motivation needs / career aspiration / occupations / machine learning

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