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