Research Topic Analysis in Engineering Management Using a Latent Dirichlet Allocation Model

Abstract

Traditional journal analyses of topic trends in IS journals have manually coded target articles from chosen time periods. However, some research efforts have been made to apply automatic bibliometric approaches, such as cluster analysis and probabilistic models, to find topics in academic articles in other research areas. The purpose of this study is thus to investigate research topic trends in Engineering Management from 1998 through 2017 using an LDA analysis model. By investigating topics in EM journals, we provide partial but meaningful trends in EM research topics. The trend analysis shows that there are hot topics with increasing numbers of articles, steady topics that remain constant, and cold topics with decreasing numbers of articles.