Cultural Pulse: Employee Sentiment Analysis of Employee Perceptions of Organisational Culture and Work Life Balance in Indian Corporates

Abstract

This study proposes CulturePulse, a hybrid Natural Language Processing (NLP) and Machine Learning (ML) framework for analysing employee sentiment towards organisational culture and work-life balance in Indian corporates. The study analyses 544 employee reviews collected from 26 companies using VADER-based sentiment scoring and workplace dimensions such as salary, culture, job security, work-life balance, and work satisfaction.

Among the evaluated models, Logistic Regression achieved the highest performance with 94.95% accuracy and a 5-fold cross-validation score of 0.985. Findings indicate that work satisfaction is the strongest predictor of overall employee sentiment, while salary shows comparatively lower predictive influence despite frequent mention in reviews. The framework further identifies variations in employer brand strength and retention risk across firms.

The study contributes a scalable NLP–ML framework for employee sentiment analytics and advances HR analytics research in the Indian corporate context.