Abstract

ABSTRACT This study uses Natural Language Processing (NLP) to analyze 110 articles from the Scopus database (2018–2023). Employing TextBlob for preprocessing and sentiment analysis, and Latent Dirichlet Allocation (LDA) for topic modeling, the research explores evolving themes in smart library abstracts. Key findings highlight a shift toward user-centricity, technological integration, and emerging concepts like Internet of Things (IoT) and Artificial Intelligence (AI). Sentiment analysis shows a generally positive outlook for this evolution. The study provides valuable insights for researchers and practitioners, guiding future innovation and service design in smart libraries.

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