Co-mention network of R packages: Scientific impact and clustering structure

作者：

Highlights：

• We analyzed the co-mention pattern of all R packages in 13,684 PLoS journal papers that cite R.

• We find that the discipline and function of the packages can partly explain the largest clusters of the co-mention network.

• We use three major centrality measures and the total count to evaluate the importance of R packages.

摘要

•We analyzed the co-mention pattern of all R packages in 13,684 PLoS journal papers that cite R.•We find that the discipline and function of the packages can partly explain the largest clusters of the co-mention network.•We use three major centrality measures and the total count to evaluate the importance of R packages.

论文关键词：R,Open software,Scientometrics,Network analysis,Co-mention analysis

论文评审过程：Received 8 November 2017, Revised 30 November 2017, Accepted 1 December 2017, Available online 5 December 2017, Version of Record 5 December 2017.

论文官网地址：https://doi.org/10.1016/j.joi.2017.12.001