Journal of Information Resources Management ›› 2020, Vol. 10 ›› Issue (3): 70-77.doi: 10.13365/j.jirm.2020.03.070

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Analysis and Visualization of Research Topic Evolution Based on S-curve

Zhang Wandi1 Hu Zhigang1 Guo Jiacheng1 Du Peng2   

  1. 1. Institution of Science of Science and S.& T. Management, Daliian University of Technology, Dalian 116024; 2.Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100081
  • Online:2020-05-26 Published:2020-05-26

Abstract: Visualization research on the evolution trend of research topic can contribute to the identification of the research evolution stage and core content, also can intuitively show the evolution pattern of the discipline field. Firstly, the research topic is analyzed by keyword co-occurrence network, and the clustering results obtained by VOSviewer can be used to identify the research topic. Secondly, based on Logistic model and temporal information, regression analysis and the value of topic maturity are calculated from the clustering results of theme co-occurrence. Using S curve to fit the growth curve of research theme can realize the grasp and prediction of research topic evolution.

Key words: Logistic curve, Cluster analysis, Topic identification, Theme evolution, Mapping knowledge domain

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