Like many professional work activities in this age of ubiquitous computing and high-speed internet connections, computer programming and software development are increasingly mediated by systems with ‘social media’ features like profiles, avatars, ‘liking’, and commenting capabilities. When working on shared tasks, programmers have effectively leveraged these capabilities to overcome differences in time and location while simultaneously using collaborative web applications, such as version control repositories like SCM or ‘git’ systems to work together more efficiently. Here we present preliminary findings from a project investigating patterns of collaboration on the social coding platform Github. We've used a research method that combines the use of statistical approaches from social network analysis (SNA) and traditional qualitative case study construction. Our results show that this method is useful in qualitatively explaining the topology of a collaborative network, especially the formation of cliques that have been identified using traditional SNA metrics.