2026-05-13T16:15:02.788Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:3:11180 2025-06-13T13:58:39Z 3

Using Text Mining to Identify Employee Dissatisfaction Optimized by Modified Metaheuristics, Chapter in AIS Algorithms for Intelligent Systems: PCCDA 2024: International Conference on Paradigms of Communication, Computing and Data Analytics, Springer 2025 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/3/11180 https://link.springer.com/chapter/10.1007/978-981-97-7946-8_1 V. Mizdrakovic L. Jovanovic M. Zivkovic M. Antonijevic J. Kaljevic N. Bacanin This study delves into the critical realm of employee satisfaction, a subject of paramount importance to corporate managers and leaders. The research proposes an innovative methodology employing natural language processing (NLP) to assess employee sentiment towards an organization through the effective analysis of feedback. The approach incorporates the AdaBoost classifier to discern sentiment encoded utilizing the term frequency-inverse document frequency (TF-IDF) strategy. To enhance classification precision, metaheuristic optimizers are implemented. Moreover, a tailored variant of the SCA metaheuristics has been created to address the weaknesses of the elementary version, aligning it with the specific requirements of this study. The meticulously crafted models demonstrate remarkable performance, achieving a classification accuracy surpassing 88% when verified on a publicly accessible real-world dataset. This research not only contributes a practical and effective approach to gauging employee satisfaction but also showcases the efficacy of combining NLP, machine learning classifiers, and metaheuristic optimization techniques for insightful organizational sentiment analysis. bookPart Springer, Singapore 1 14 10.1007/978-981-97-7946-8_1 AIS Algorithms for Intelligent Systems: PCCDA 2024: Proceedings of International Conference on Paradigms of Communication, Computing and Data Analytics