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

Abstract

The purpose of this study is to explore the subject structure and hidden knowledge and development of new research subjects. This research is applied from the point of purpose and type, descriptive and from the point of method, trend analysis. The population of this study is the all of articles indexed in Scopus and written by Iranian authors in the field of knowledge and information science from 1992-2019, Then take the targeted sample in 2008-2019.Data analysis tool is software R which abstract the papers were analyzed after applying pre - processing steps with Topic modeling and LDA algorithm. The result of study to identification topic development process showed Hot topics & Cold topics to identifying the process of knowledge and information science by determining the p-level (0/05) and identify alpha, beta and theta parameters. The Hot topics that have a more popularity is: Library services on Social Networks, Research Models, Social Capital, Data Base, Data Mining, Trend of Scientific Publication, Interdisciplinary Fields, Cyberspace Algorithms, Knowledge Management and Cold topic that have a less popularity is: Electronic Resources, Information management System, Search Engine, Book loan Services, Distance Library Services, E learning, E Government, Journal Evaluation Indicators, Web sources Evaluation, Digital Library. The result of this research showed that the field of knowledge and information science can growth up with globalization and new global issues and this field ability to develop and expand in data mining, artificial intelligence, semantic retrieval, information architecture, digital publishing, social networking and information technology.

Keywords

• topic modeling
• lda
• trend analysis
• hot topic
• cold topic
• log-likelihood
• knowledge and information science
• text mining