A Data-Driven Approach for Discovering the Recent Research Status of Diabetes in China

Abstract

This paper aims at discovering the recent research status of diabetes in China through a data-driven bibliometrics and knowledge mapping analysis method on diabetes-related literature. With the basis of 24,561 publication documents from CNKI during 2007–2016, the quantitative analysis are conducted in three aspects: (1) descriptive statistical method for acquiring literature distribution characteristics; (2) hierarchical clustering, k-means clustering analysis, and multidimensional scaling analysis based on a keyword co-occurrence matrix for discovering research hotspots; and (3) network analysis for revealing cooperation relationships among authors and affiliations. The result shows some findings about the recent diabetes research in China. It also demonstrates the close cooperation of diabetes research among productive authors and affiliations through network generation and visualization.