Thematic Analysis of Iranian Medical Library and Information Theses and Dissertations: Applying Text Mining Techniques
With the development of Internet technology, the amount of data has increased astonishingly. This article aims to determine the thematic trend of theses and dissertations in librarianship of postgraduate courses in the universities of medical sciences. The study analyzed 110 theses from five Iranian...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Regional Information Center for Science and Technology (RICeST)
2025-04-01
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| Series: | International Journal of Information Science and Management |
| Subjects: | |
| Online Access: | https://ijism.isc.ac/article_722617_ac90333f33b32372803352c038fe4b45.pdf |
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| Summary: | With the development of Internet technology, the amount of data has increased astonishingly. This article aims to determine the thematic trend of theses and dissertations in librarianship of postgraduate courses in the universities of medical sciences. The study analyzed 110 theses from five Iranian universities in Medical Library and Information Science (MLIS) between 2017 and 2021. A Python script processed Persian text to create a word cloud and extract significant keywords using TF-IDF. Data was preprocessed, normalized, and filtered, and keywords were grouped by year and university for analysis. Results show key research topics in MLIS from 2017 to 2021, including information-seeking behavior, Altmetrics, health, and information services, as shown in the word cloud. Common themes included information-seeking behavior, digital literacy, and health literacy, indicating stable research trends in medical library science topics. Each university emphasized different areas: Isfahan focused on clinical aspects, Tehran on foundational issues, Shahid Beheshti on scientometrics, while Hamadan addressed information retrieval. Trends showed limited variation in keywords over the years. The study highlights evolving Medical Library and Information Science (MLIS) topics, emphasizing a shift towards patient information and health literacy. However, a gap exists in addressing issues like AI and big data. Limited collaboration and data hindered the research scope, suggesting that future studies should explore faculty and student topic selection interests. |
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| ISSN: | 2008-8302 2008-8310 |