2.3. Statistical analysis

CiteSpace, built on scientometrics and data visualization analysis, was designed by Drexel University Professor Chaomei Chen in Java,^[33] which helps researchers to analyze the research field quantitatively and qualitatively and can improve our understanding of the research field. For example, CiteSpace computationally identifies critical points in the literature and highlights them in a visual network; by constructing a complex visual network of keywords or literature to highlight the development process and future trends of a specialty in a comprehensive way; by exploding words to indicate the research frontiers in the field under study at various periods.^[34] Leiden University’s Science and Technology Research Center created VOSviewer, a scientometric technology network analysis tool. VOSviewer can build views based on web-based literature data in keywords, journals, institutions, authors, etc. It can be displayed in up to 3 or 4 ways, such as label view, density view, cluster density view, and scatter view.^[35] It is characterized by graphical representation, which makes the data easy to understand, especially for some large maps.^[34] We used Microsoft Excel 2016 (Redmond, WA) to enumerate the obtained data and used Excel functions to present these data in tables or graphs. We used the following metrics to assess research results: (1) count, for example, number of publications, keyword co-occurrence network, and number of citations to the literature. (2) Betweenness centrality, (3) degree, (4) burst, and (5) citation tree-rings.