Network of R packages: A characterization of an empirical collaborative network

Abstract

We analyze the evolution of the main package library of the programming language R, a free and open-source software used in Statistics, Economics, Machine Learning, Geography, and many other fields. R-packages are self-contained pieces of the software that can relate to each other through dependency and suggestion relationships, giving rise to empirical collaborative networks that have grown significantly in the last twenty years. The dependency network connects two packages if one requires another, and the suggestion network connects packages if there are examples using them together. Each network's structure is composed by two main groups: the biggest connected component (BCC) and the set of independent packages, isolated from the rest. We characterize how new packages enter the network in terms of the number of connections they incorporate, and the packages they connect to. The number of incorporated connections follows a log-normal distribution, whose scale is linear on the fraction of packages in the BCC. We characterize to which packages the incomers connect to in terms of preferential attachment, finding super-linear preferential attachment in both networks. We provide a detailed characterization of the network's evolution, and point possible links to the history of the R community. The constructed dataset with the networks at different times is freely available through a public repository.