The shift in research trends related to artificial intelligence in library repositories during the coronavirus pandemic

Abstract

Purpose

This study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two topics during the coronavirus pandemic.

Design/methodology/approach

The study gathered secondary data from the Scopus website using the keywords “AI,” “library” and “repository,” from 1993 to 2022. Data were re-analyzed using the bibliometric software VOSviewer to examine the trending country's keyword relations and appearance and Biblioshiny to study the publication metadata.

Findings

Index keywords, such as “human,” “deep learning,” “machine learning,” “surveys” and “open-source software,” became popular during 2020, being closely related to digital libraries. Additionally, the annual scientific production of papers increased significantly in 2021. Words related to data mining also had the most significant growth from 2019 to 2022 because of the importance of data mining for library services during the pandemic.

Practical implications

This study provides insight for librarians for the implementation of AI to support repositories during the pandemic. Librarians can learn how to maximize the AI-based repository services in academic libraries during the pandemic. Furthermore, academic libraries can create policies for repository services using AI.

Social implications

This study can lead researchers, academicians and practitioners in conducting research on AI in library repositories.

Originality/value

As research on AI and digital repositories remains limited, the study identifies themes and highlights the knowledge gap existing in the field.

Citation

Nugroho, P.A., Anna, N.E.V. and Ismail, N. (2023), "The shift in research trends related to artificial intelligence in library repositories during the coronavirus pandemic", Library Hi Tech, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/LHT-07-2022-0326