Detecting emerging Trends in Articles on Iranian Medical librarianship and Information Using the TFIDF Algorithm

The present study identifies emerging trends in medical library and information science articles published in Iranian scientific-research journals. This exploratory research analyzes medical library and information science articles published in this field’s journals in Iran from 1997 to 2020 using text mining techniques. The TF-IDF algorithm was employed to identify the most important terms used in the articles. Python programming language was utilized to implement the text mining algorithms. The examination of emerging terms in articles published in medical library and information science journals indicates that terms such as LibQUAL, practical, and bibliotherapy have recently entered the articles and studies of this field in domestic journals during the period from 2005 to 2015. Similarly, terms like invention, altmetrics, and repository have recently appeared in the articles and studies of this field in domestic journals during the period from 2015 to 2020. The results indicate that the terms used in medical library and information science articles have not remained constant over time and have undergone changes during different periods. This reflects that, in line with the emergence and growth of technology, this scientific field has also evolved.