Emotion Perception and Service Optimization in ChatGPT-Driven Smart Libraries

[Purpose/Significance] Sentiment analysis technology is an important part of the natural language process and plays a key role in modern smart systems. As smart libraries continue to develop, traditional service models focused only on functionality are no longer enough to meet users' diverse and personalized needs. In the digital transformation era, smart libraries need new technologies to improve service quality, and adding sentiment awareness has become a key way to move beyond traditional approaches. This study uses ChatGPT(Chat Generative Pre-trained Transformer) to apply sentiment analysis in smart library services. This goal is to create a new service model based on emotions, helping smart libraries shift from basic information management to services that focus on emotional care and better user experiences. This approach not only helps smart libraries handle the challenges of digital transformation but also offers a fresh way to meet users' emotional needs. [Method/Process] This study reviews relevant literature from both domestic and international sources, systematically analyzing the mainstream research methods and technological trends in the field of smart libraries. It also explores the adaptability and feasibility of sentiment analysis technology in smart libraries, based on current practical scenarios. The research uses ChatGPT's sentiment analysis as the technological foundation, combined with the theory of smart library service models, leveraging the advantages of the ChatGPT to create an analysis framework that integrates theory and practice. At the same time, the study draws on successful cases and practical experiences from domestic and international smart libraries, such as intelligent recommendation systems and contextual knowledge services, extracting effective application paths for sentiment perception technology. This approach provides strong theoretical and practical support for the applicability of the research methods, ensuring the scientific, logical, and innovative nature of the study, and effectively contributing to the optimization of smart library services. [Results/Conclusions] ChatGPT's sentiment analysis capabilities have the potential to significantly enhance both the service quality and user experience in smart libraries. Personalized recommendations and context-aware services can effectively meet the diverse needs of library users. However, the application and research in this area are still in their infancy in China, and there are ongoing challenges in technology adaptation and practical implementation. Particularly, the difficulties in promoting the technology, user adaptability, and issues related to funding have hindered the implementation and widespread adoption of smart library services. To promote the further development of smart libraries, greater efforts should be made to deepen the integration of ChatGPT technology and explore its potential to meet the evolving demands for library services in the digital era. Additionally, the research proposes strategies to address these challenges, such as enhancing technology adaption and user education, exploring diversified funding support options, and continuously innovating application pathways. Through these explorations, smart libraries will better adapt to the needs of the new era and provide more personalized, context-aware services.