An empirical exploration of the diversified R ecosystem

Born in the late 20th century, R has become one of the most widely used software environments for statistical computing and graphics, undergoing substantial transformation alongside advances in information technology and the rise of data-intensive research. By integrating large-scale usage data from the Comprehensive R Archive Network (CRAN) with bibliometric records from the Scopus database, this study provides a comprehensive empirical review of the R ecosystem between 2005 and 2024. We examine long-term trends in R adoption, the functional structure and popularity patterns of its package ecosystem, disciplinary applications in academia, and collaboration behaviors within the developer community. The results reveal sustained growth in both R software and package downloads, with package usage showing more stable and continuous expansion over time. A keyword co-occurrence analysis indicates that the ecosystem is organized around a dense statistical core, closely connected with diverse modeling frameworks, modern machine learning techniques, and application-oriented functionalities. Bibliometric evidence further demonstrates the widespread and growing adoption of R across scientific disciplines, particularly in agricultural and biological sciences, environmental science, medicine, and the social sciences. In addition, collaboration analysis shows that multi-author packages are more prevalent and tend to achieve greater reuse and higher download activity, highlighting the role of collective development in sustaining the vitality and long-term relevance of the R ecosystem. Overall, these findings position R as a resilient, community-driven platform whose evolution continues to be shaped by interdisciplinary collaboration and open-source innovation.