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              <text>Uncovering User Attitudes and Satisfaction Levels with HRMS Applications: Insights from Sentiment Analysis</text>
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              <text>Human Resource Management System (HRMS); NLP; NLTK; Sentiment analysis; User interface</text>
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              <text>This study examines employee perspectives on various features and specifications of Human Resource Management System (HRMS) applications, as expressed in online discussion boards. An in-depth literature review was conducted to identify key factors, followed by topic modeling on unstructured text data. Sentiment analysis using the Li-Hu method and a tweet profile helped gauge employee satisfaction with HRMS applications. The findings suggest a moderate level of satisfaction among users, offering insights for companies to enhance user interfaces and software development. By addressing negative attitudes and fostering positive ones, businesses can cultivate better relationships with users. This research also aids in identifying top-performing HRMS applications in the market, highlighting the features and specifications that set them apart from competitors. Overall, the study serves as a valuable resource for organizations aiming to improve their HRMS offerings and user experiences.   2024 IEEE.</text>
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              <text>Srivastava J.; Priyadarsini K.</text>
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              <text>TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/TQCEBT59414.2024.10545119" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/TQCEBT59414.2024.10545119&lt;/a&gt;
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              <text>ISBN: 979-835038427-7</text>
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              <text>Srivastava J., Christ University, India; Priyadarsini K., Psgim, India</text>
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