Leveraging People Analytics for Employer Branding: A Text Mining Study of Employee Reviews in IT Industry

Journal of Chinese Human Resource Management. 2025. Vol. 16. No. 2. P. 97–120.

Mahar D. H.

The rise of crowdsourced job reviews has provided valuable insights into employer branding. This study applies text-mining techniques to analyse employee reviews and identify key employer value propositions (EVPs) in the U.S. IT industry. A dataset of 21,482 employee reviews from 11 Fortune 500 IT companies was collected from Indeed. com, followed by bigram analysis and Structural Topic Modeling (STM) for extracting recurring themes and sentiments. The bigram analysis identified work-life balance and competitive compensation as the most positively associated factors, whereas job security emerged as the most frequently criticized aspect. The STM analysis identifies five dominant EVPs that IT professionals prioritize. Further, findings indicate a growing emphasis on management quality and economic value over time, while employee joy at work has declined since 2012. These insights have practical implications for HR managers and policymakers aiming to enhance employer branding strategies. This study contributes to the field of people analytics by integrating computational textmining methods to analyse employee feedback, offering a data-driven approach to understanding workforce sentiments. Limitations and future research directions are discussed in relation to expanding the study across different industries and geographical contexts.

Keywords: ИТ-индустрия, people analytics, интеллектуальный анализ текста (text mining), IT industry, employer value propositions, text mining, employer branding, аналитика персонала, брендинг работодателя, ценностные предложения работодателя