{"title":"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","authors":"Abhijit Thakuria, Dipen Deka","doi":"10.1007/s11192-024-05058-4","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"126 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach\",\"authors\":\"Abhijit Thakuria, Dipen Deka\",\"doi\":\"10.1007/s11192-024-05058-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":21755,\"journal\":{\"name\":\"Scientometrics\",\"volume\":\"126 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientometrics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s11192-024-05058-4\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientometrics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11192-024-05058-4","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach
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.
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.