A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach

IF 3.5 3区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Scientometrics Pub Date : 2024-06-03 DOI:10.1007/s11192-024-05058-4
Abhijit Thakuria, Dipen Deka
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Abstract

The study utilized Latent Dirichlet Allocation (LDA) Topic modeling to identify prevalent latent topics within Open Access (OA) Library and Information Science (LIS) journals from 2013 to 2022. Eight core OA Scopus indexed journals were selected based on their SJR scores and DOAJ listing. Titles, Abstracts and keywords of 2589 articles were extracted from the Scopus database. R software packages were used to perform data analysis and LDA topic modeling. The optimal value of k was determined to be 9. The analysis revealed that 53.89% of documents comprise over 50% of a certain topic (θ > 0.50). Notably, ‘Scholarly Communication’ and ‘Information Systems, Models and Frameworks’ emerged as dominant topics with the highest proportions of research literature in the corpus. The topic ‘Scholarly Communication’ experienced significant growth with an average annual growth rate (AAGR) of 4.37%, while ‘Collection development and E-resources’ exhibited the lowest research proportion and a negative AAGR of − 4.22%. Additionally, topics such as ‘Information Seeking Behaviour and User Studies’, ‘User Education and Information Literacy’, and ‘Information Retrieval and Systematic Review’ remained stable and persistent topics. Conversely, research on traditional topics like ‘Librarianship and Profession’, ‘Bibliometrics’ and ‘Medical Library and Health Information’ showed a gradual decline. The LDA topic modeling approach unveiled previously unknown or unexplored topics in open access LIS research literature, enhancing our understanding of emerging trends.

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利用主题建模方法识别开放获取的 LIS 期刊中的潜在主题和研究趋势的十年期研究
本研究利用潜狄利克特分配(LDA)主题建模来识别 2013 年至 2022 年开放获取(OA)图书馆与信息科学(LIS)期刊中的流行潜主题。根据其 SJR 分数和 DOAJ 列表,选择了八种核心 OA Scopus 索引期刊。从 Scopus 数据库中提取了 2589 篇文章的标题、摘要和关键词。使用 R 软件包进行数据分析和 LDA 主题建模。k 的最佳值被确定为 9。分析结果显示,53.89%的文档包含超过 50%的特定主题(θ >0.50)。值得注意的是,"学术交流 "和 "信息系统、模型和框架 "是语料库中研究文献比例最高的主导主题。学术交流 "专题的年均增长率(AAGR)为 4.37%,增长显著,而 "馆藏开发与电子资源 "专题的研究比例最低,年均增长率为负 4.22%。此外,"信息搜索行为与用户研究"、"用户教育与信息素养 "和 "信息检索与系统综述 "等主题仍然是稳定而持久的主题。相反,"图书馆学与专业"、"文献计量学 "和 "医学图书馆与健康信息 "等传统主题的研究则逐渐减少。LDA 主题建模方法揭示了开放存取 LIS 研究文献中以前未知或未探索的主题,增强了我们对新兴趋势的理解。
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来源期刊
Scientometrics
Scientometrics 管理科学-计算机:跨学科应用
CiteScore
7.20
自引率
17.90%
发文量
351
审稿时长
1.5 months
期刊介绍: Scientometrics aims at publishing original studies, short communications, preliminary reports, review papers, letters to the editor and book reviews on scientometrics. The topics covered are results of research concerned with the quantitative features and characteristics of science. Emphasis is placed on investigations in which the development and mechanism of science are studied by means of (statistical) mathematical methods. The Journal also provides the reader with important up-to-date information about international meetings and events in scientometrics and related fields. Appropriate bibliographic compilations are published as a separate section. Due to its fully interdisciplinary character, Scientometrics is indispensable to research workers and research administrators throughout the world. It provides valuable assistance to librarians and documentalists in central scientific agencies, ministries, research institutes and laboratories. Scientometrics includes the Journal of Research Communication Studies. Consequently its aims and scope cover that of the latter, namely, to bring the results of research investigations together in one place, in such a form that they will be of use not only to the investigators themselves but also to the entrepreneurs and research workers who form the object of these studies.
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