Analyzing the Social Networks of Contributors in Open Source Software Community

Abstract

We conduct an extensive statistical analysis on the social networks of con- tributors in Open Source Software (OSS) communities using datasets collected from two most fast-growing OSS social interaction sites, Github.com and Ohloh.net. Our goal is to analyze the connectivity structure of the social networks of contributors and to investigate the effect of the different social ties structures on developers’ overall productivity to OSS projects. We, first, analyze the general structure of the social networks, e.g., graph distances and the degree distribution of the social networks. Our social network structure analysis confirms a power-law degree distribution and small-world characteristics. However, the degree mixing pattern shows that high degree nodes tend to connect more with low degree nodes suggesting a collaboration between experts and newbie developers. We further conduct the same analysis on affiliation networks and find that contributors tend to participate in projects of simi- lar team sizes. Second, we study the correlation between various social factors (e.g., closeness and betweenness centrality, clustering coefficient and tie strength) and the productivity of the contributors in terms of the amount of contribution and commit- ment to OSS projects. The analysis is conducted under the contexts of global and local networks, where a global network analysis considers a developer’s connectivity in the whole OSS community network, whereas a local network analysis considers a developer’s connectivity within a team network that is affiliated to a project. The analysis demonstrates evident influence of the social factors on the developers’ over- all productivity.