Mining the voice of employees: A text mining approach to identifying and analyzing job satisfaction factors from online employee reviews

Abstract

Abstract Online reviews have become a significant information source for business practitioners to know about customers opinions of their products or services. Previous studies examined product or service satisfaction factors of customers by analyzing online consumer reviews. However, examining job satisfaction factors of employees through online employee reviews has rarely been studied. In this study, we first identified job satisfaction factors from 35,063 online employee reviews posted on jobplanet.co.kr using Latent Dirichlet Allocation (LDA). Then, we conducted a series of analyses based on the factors. We measured the sentiment and importance of each job satisfaction factor at industry, company, group, and chronological levels. Dominance analysis examined the relative importance of each star-rated job satisfaction factor on overall job satisfaction. Further, the association strength between each job satisfaction factor and overall job satisfaction is computed from correspondence analysis. The results from this study will provide business managers with profound insights into making decisions on managing job satisfaction of their employees in various aspects.