تحول پژوهش‌های هوش مصنوعی در کتابخانه‌های دانشگاهی: تحلیل علم‌سنجی ساختار دانشی و روندهای تکاملی

Purpose: Artificial intelligence (AI) has emerged as one of the most influential technologies of the twenty-first century, with far-reaching implications for industries, services, and research practices. In the field of library and information science, AI is increasingly viewed as a key enabler of innovation, operational efficiency, and user-centered service delivery. Academic libraries, as central knowledge infrastructures within higher education systems, have begun to adopt a wide range of AI-based tools and applications, including intelligent information retrieval systems, automated cataloging and classification, recommendation systems, chatbots, and data-driven decision-support mechanisms. These developments have the potential to transform traditional library functions and redefine the strategic role of academic libraries in teaching, research, and knowledge management. Despite the rapid expansion of scholarly publications in this area, existing studies are often fragmented and focus on specific technologies or localized applications, resulting in a limited understanding of the overall intellectual structure, thematic evolution, and research dynamics of AI in academic libraries. Addressing this gap, the present study provides a comprehensive scientometric analysis of the global research landscape on artificial intelligence in academic libraries.
Methodology: This study adopts a bibliometric and scientometric research design to systematically examine the development, structure, and trends of scholarly literature in this domain. Data were retrieved from the Scopus database, one of the most comprehensive and widely used indexing systems for peer-reviewed scientific publications. The dataset consists of 595 documents published between 1987 and 2025 that explicitly address artificial intelligence in the context of academic libraries. A long-term time span of thirty-eight years was selected to capture both early foundational studies and recent advances in the field. Bibliographic information, including authorship, institutional affiliations, publication sources, keywords, and citation indicators, was extracted and carefully verified to ensure relevance and accuracy. The data were analyzed using specialized bibliometric software tools, including Bibliometrix and its web interface Biblioshiny, VOSviewer, and BibExcel. These tools enabled the examination of publication growth patterns, authorship and collaboration structures, country and institutional contributions, co-authorship networks, co-word relationships, thematic evolution, and citation impact.
Findings: developed from 1987 to 2025 with the publication of 598 scientific documents, 196 sources, and the participation of 1,378 authors. An annual growth rate of 1.05% reflects a steady development, characterized by an average of 2.64 authors per paper and 14.55% international collaboration, highlighting a tendency toward team-based research and cross-border interaction. Geographically, the United States leads with 126 articles (21%) followed by China with 105 articles (17.6%), while countries such as Nigeria (26 articles), India (33 articles), Pakistan (24 articles), and South Africa (23 articles) have made significant contributions to knowledge production. Universities such as the University of South Africa and The Islamia University of Bahawalpur each have the highest scientific output with 10 articles. Regarding publication sources, the Journal of Academic Librarianship stands out as the most important scientific outlet with 58 articles and citation metrics of CiteScore 6.0, SJR 0.975, and SNIP 1.627. The co-word network reveals four main clusters: technology, data analytics, human factors, and innovation, indicating the complexity and multidimensionality of the field. The thematic map shows foundational topics such as “Artificial Intelligence” and “Digital Libraries” positioned in the Motor Themes quadrant with high research cohesion, while emerging topics like “Generative AI,” “ChatGPT,” and “Information Literacy” are highlighted in the Emerging Themes quadrant. Advanced specialized subjects such as federated learning and adversarial learning are placed in the Niche Themes quadrant, indicating the future trajectory of technology in this domain. Overall, these data indicate that the field of artificial intelligence in academic libraries is transitioning from digitization to deep intelligent systems, where emerging technologies play a broad role in the production, management, and evaluation of information.
Conclusion: Overall, the results demonstrate that research on artificial intelligence in academic libraries is undergoing a significant transition from basic digitalization toward more advanced and intelligent systems. This transformation reflects broader changes in how libraries conceptualize their role in supporting research, learning, and knowledge creation. Beyond improving operational efficiency, AI is increasingly associated with strategic decision-making, personalized services, and new ethical and professional challenges. The findings of this study offer a comprehensive overview of the current state and evolution of AI research in academic libraries and provide valuable insights for researchers, library managers, and policy makers seeking to understand the intellectual landscape, identify research gaps, and anticipate future developments in this rapidly evolving field.