TY - JOUR
T1 - The shift in research trends related to artificial intelligence in library repositories during the coronavirus pandemic
AU - Nugroho, Prasetyo Adi
AU - Anna, Nove E.Variant
AU - Ismail, Noraini
N1 - Publisher Copyright:
© 2023, Emerald Publishing Limited.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Artificial intelligence (AI)
KW - Coronavirus (COVID-19)
KW - Developing countries
KW - Knowledge sharing
KW - Library
KW - Repository
UR - http://www.scopus.com/inward/record.url?scp=85152930879&partnerID=8YFLogxK
U2 - 10.1108/LHT-07-2022-0326
DO - 10.1108/LHT-07-2022-0326
M3 - Article
AN - SCOPUS:85152930879
SN - 0737-8831
JO - Library Hi Tech
JF - Library Hi Tech
ER -