In this paper, we seek to identify the factors that influence the impact of open source software (OSS) on users community through the analysis of the evolution of the OSS network. Based on longitudinal data collected from the comprehensive R archive network (CRAN), we empirically examine how the network of R packages evolves over time and exert its influence on the scientific community. We find that critical network features derived from CRAN, such as pagerank, closeness, and betweenness centralities, play a significant role in determining the impact of each package on the research and publication activities in the scientific community. Furthermore, the performance of R packages can be explained as a flow of information from the core to the periphery that exhibits strong spillover effects. (CC BY-NC-ND 4.0) probability for actors to be included into an exchange of information which, in turn, is instrumental in assessing the level of influence of each node in the communications at a local level and across the whole network. The directional patterns of the communication describe how information moves around and how much actors can facilitate or control the flow. A number of aspects of information can be studied using approaches in social network analysis, including information needs, information exposure, information flow, information control, and information opportunities [22]. As discussed in the introduction, the major drawback of the social network approach lies in its cyclic nature. In our case, a cyclic network characterization is not possible due to the nature of the relationships between packages. In