Bibliometric assessment of artificial intelligence applications in libraries

Insights of author pattern from Scopus data

Abstract

Purpose: Artificial intelligence (AI) has become a transformative technology in libraries, enabling enhanced services, information access, and personalized experiences. To understand the research trends and patterns in AI applications in libraries, a comprehensive bibliometric assessment of authorship patterns was conducted.

Methodology: Using data from the Scopus database, key authorship metrics, affiliations, corresponding authors' countries, country-level scientific production, and Lotka's Law analysis were analyzed.

Findings: The study identified influential authors, assessed their impact, examined affiliations and international collaborations, and evaluated country-level scientific production. The analysis revealed steady growth in research output, emphasizing the significance of AI in libraries. Collaboration among authors, including international collaboration, showcased the global nature of research efforts. Key authors and their contributions were identified, and patterns of productivity over time were observed. The study also highlighted the countries with the highest scientific production and their research ecosystem. The findings provide insights into authorship patterns, research impact, and global collaboration in AI applications in libraries.

Research implications: The study has implications for research policies, international collaboration, economic and social development, education, and benchmarking. By leveraging these insights, policymakers, researchers, and educators can make informed decisions to advance science and technology, foster innovation, and address global challenges in the library domain.