首页|Exploring trends and gaps in sustainable e-library research: a text mining analysis
Exploring trends and gaps in sustainable e-library research: a text mining analysis
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NETL
NSTL
Emerald Group Publishing
PurposeThis study aims to use topic modeling to identify different research dimensions of the e library research domain. This research analyses abstracts from a large set of scholarly articles to identify emerging topics and trends in sustainable e-library research to guide future efforts. These topics include those that have been studied a lot and those that need more research in the field of electronic libraries.Design/methodology/approachThe study uses text mining and latent Dirichlet allocation (LDA) to analyse abstracts from 3,223 papers published in prestigious journals between 1961 and 2024. Post-2023 articles are abundant in the data set. Identifying research themes and gaps requires data collection, text pre-processing, LDA topic modelling and visualization.FindingsThe topic modelling-LDA output reveals 15 topics, main emphasis areas for "Sustainable E-Library" research. The findings reveal differences in research trends within various elements of electronic libraries. While topics such as "e-library practices", "digital literacy in libraries", "medical record analysis", "mobile library platform", "academic content management", "technology impact studies", "semantic search approach", "virtual information environment", "digital knowledge rights", "digital research publishing" and "usability criteria analysis", have garnered significant interest, others such as "open collection architecture", "community support programs", "online information access" and "multimedia data processing" are less common. There has been a substantial increase in research publications on various subjects, particularly in the past ten years. Factors determining the popularity of articles in the e-library sector include keywords searched in Scopus, the number of citations and the publisher's name.Research limitations/implicationsThe insights gained from this study, along with the discussions on each issue, will guide researchers, academicians, journal editors and practitioners in directing their research efforts. Notably, no prior study has used an intelligent algorithm to identify research clusters within the field of sustainable e-libraries.Originality/valueThis study contributes to the field by introducing LDA to identifying research trends in sustainable e-libraries. By analysing a large data set spanning several decades, this study provides valuable insights into prevalent research themes and areas requiring further investigation within the electronic library domain. The use of modern statistical methodologies enhances the study's originality, providing researchers and practitioners with new insights for future research and practice in the field.
Digital libraryTopic modellingNatural language processing (NLP)Machine learning (ML)Latent Dirichlet allocation (LDA)Sustainable e-libraryDIGITAL RIGHTS MANAGEMENTONTOLOGYCOMMUNITYSUPPORTTOPICS
NETL
NSTL
Emerald Group Publishing
