Mapping Global Neurosurgery Research Collaboratives: A Social Network Analysis of the 50 Most Cited Global Neurosurgery Articles

Abstract

Social network analysis of bibliometric data evaluates the relationships between the articles, authors, and themes of a research niche. The network can be visualized as maps composed of nodes and links. This study aimed to identify and evaluate the relationships between articles, authors, and keywords in global neurosurgery. The authors searched global neurosurgery articles on the Web of Science database from inception to June 18, 2020. The 50 most cited articles were selected and their metadata (document coupling, co-authorship, and co-occurrence) was exported. The metadata were analyzed and visualized with VOSViewer (Centre for Science and Technology Studies, Leiden University, The Netherlands). The articles were published between 1995 and 2020 and they had a median of 4.0 (interquartile range [IQR] = 5.0) citations. There were 5 clusters in the document coupling and 10 clusters in the co-authorship analysis. A total of 229 authors contributed to the articles and Kee B. Park contributed the most to articles (14 publications). Backward citation analysis was organized into 4 clusters and co-occurrence analysis into 7 clusters. The most common themes were pediatric neurosurgery, neurotrauma, and health system strengthening. The authors identified trends, contributors, and themes of highly cited global neurosurgery research. These findings can help establish collaborations and set the agenda in global neurosurgery research.