Analyzing Employee Job Satisfaction Through Sentiment Analysis for Enhanced Workplace Improvement and Business Success

Employee satisfaction is a crucial factor affecting organizational performance, productivity, and overall workplace efficiency. This study investigates employment satisfaction through sentiment analysis, focusing on employees’ responses through the Employee Experience-Satisfaction (EmEx-Sa) questionnaire. The study employs natural language processing (NLP), and in particular the lexicon-based sentiment analysis methodology, to analyze data obtained from open and semi-open questions, multiple-choice alternatives, and demographic questions. The objective is to utilize data from sources such as the Michigan Organizational Assessment Questionnaire (MOAQ), Minneso-ta Satisfaction Questionnaire (MSQ) and Job Descriptive Index (JDI) to determine the primary el-ements that impact job satisfaction and gain insight into the attitudes and emotions of employees. The findings delineate critical factors influencing job satisfaction, encompassing the work envi-ronment, leadership quality, salary, and opportunities for professional advancement. Moreover, they demonstrate that sentiment analysis provides valuable insights into employee viewpoints, acting as a credible substitute for conventional research methods. This research enhances the un-derstanding of job satisfaction by identifying sentiment trends—positive, neutral, or negative—thereby enabling data-driven decision-making for organizational enhancement. The research un-derscores the significance of internal marketing tactics in fostering engagement, trust, and trans-parency between management and employees. The findings provide actionable suggestions for boosting working conditions, fostering employee well-being, and improving organizational per-formance, underscoring the strategic imperative of prioritizing job satisfaction.