Journal article
Co-mention network of R packages: Scientific impact and clustering structure
Journal of informetrics, v 12(1), pp 87-100
Feb 2018
Abstract
•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.
Despite its rising position as a first-class research object, scientific software remains a marginal object in studies of scholarly communication. This study aims to fill the gap by examining the co-mention network of R packages across all Public Library of Science (PLoS) journals. To that end, we developed a software entity extraction method and identified 14,310 instances of R packages across the 13,684 PLoS journal papers mentioning or citing R. A paper-level co-mention network of these packages was visualized and analyzed using three major centrality measures: degree centrality, betweenness centrality, and PageRank. We analyzed the distributive patterns of R packages in all PLoS papers, identified the top packages mentioned in these papers, and examined the clustering structure of the network. Specifically, we found that the discipline and function of the packages can partly explain the largest clusters. The present study offers the first large-scale analysis of R packages’ extensive use in scientific research. As such, it lays the foundation for future explorations of various roles played by software packages in the scientific enterprise.
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Details
- Title
- Co-mention network of R packages: Scientific impact and clustering structure
- Creators
- Kai LiErjia Yan
- Publication Details
- Journal of informetrics, v 12(1), pp 87-100
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000427479800007
- Scopus ID
- 2-s2.0-85036465995
- Other Identifier
- 991014976885404721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science