an article by Jinho Choi (Sejong University, Seoul), Sangyoon Yi (University of Southern Denmark) and Kun Chang Leec (Sungkyunkwan University, Seoul) published in Information & Management Volume 48 Issue 8 (December 2011)
Abstract
New concepts and ideas build on older ones. This path dependence in knowledge evolution has promoted research to identify important knowledge elements, research trends, and opportunities by analysing publication data. In our study, keyword networks formed from published academic articles were analysed to examine how keywords are associated with each other and to identify important keywords and their change over time.
Based on MIS publication data from 1999 to 2008, our analysis provided several notable findings.
First, while the MIS field has changed rapidly, resulting in many new keywords, the connectivity among them is highly clustered.
Second, the keyword networks show clear power-law distribution, which implies that the more popular a keyword, the more likely it is selected by new researchers and used in follow-on studies. In addition, a strong hierarchical structure is identified in the network.
Third, the network-based perspective reveals interdisciplinary keywords which are different from popular ones and have the potential to lead research in the MIS field.
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