User influence analysis for Github developer social networks

Github, one of the largest social coding platforms, offers software developers the opportunity to engage in social activities relating to software development and to store or share their codes/projects with the wider community using the repositories. Analysis of data representing the social interactions of Github users can reveal a number of interesting features. In this paper, we analyze the data to understand user social influence on the platform. Specifically, we propose a Following-Star-Fork-Activity based approach to measure user influence in the Github developer social network. We first preprocess the Github data, and construct the social network. Then, we analyze user influence in the social network, in terms of popularity, centrality, content value, contribution and activity. Finally, we analyze the correlation of different user influence measures, and use Borda Count to comprehensively quantify user influence and verify the results.