Identification of Topic Development Process of Knowledge and Information Science Field Based on the Topic Modeling (LDA)

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Abstract

The purpose of this study is to explore the thematic trend analysis of Iranian articles in Library and Information Science based on Topic modeling (LDA) and linear regression model. The population of this study consists of 709 articles indexed in Scopus during 2008-2009. In order to achieve the research objectives, the data were analyzed using text mining algorithms, especially LDA thematic modeling algorithms using R software. The results showed that among the extracted topics, there are topics that have high research popularity and are considered as hot topics. These topics include library services on social media, research models, social capital, medical databases, data mining, scientific production trends, interdisciplinary studies, cyberspace algorithms, knowledge management, social media studies, research approaches, and future studies. Also, topics that are less popular and are considered as cold topics include areas such as electronic resources, information management system, search engines, book loan services, distance services, e-learning, e-government, journal evaluation indicators, evaluation of web resources, and digital libraries. The results indicated that Library and Information Science research in Iran has developed in line with the growth of technologies and global topics and has established the relationship between Library  and Information Science subject area and new fields of data mining, artificial intelligence, semantic retrieval, ontologies, information architecture, digital publishing, social networks, and databases.

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