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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.

Open collaboration systems, such as Wikipedia, need to maintain a pool of volunteer contributors to remain relevant. Wikipedia was created through a tremendous number of contributions by millions of contributors. However, recent research has shown that the number of active contributors in Wikipedia has been declining steadily for years and suggests that a sharp decline in the retention of newcomers is the cause. This article presents data that show how several changes the Wikipedia community made to manage quality and consistency in the face of a massive growth in participation have ironically crippled the very growth they were designed to manage. Specifically, the restrictiveness of the encyclopedia’s primary quality control mechanism and the algorithmic tools used to reject contributions are implicated as key causes of decreased newcomer retention. Furthermore, the community’s formal mechanisms for norm articulation are shown to have calcified against changes—especially changes proposed by newer editors.

Many quantitative, log-based studies of participation and contribution in CSCW and CMC systems measure the activity of users in terms of output, based on metrics like posts to forums, edits to Wikipedia articles, or commits to code repositories. In this paper, we instead seek to estimate the amount of time users have spent contributing. Through an analysis of Wikipedia log data, we identify a pattern of punctuated bursts in editors' activity that we refer to as edit sessions. Based on these edit sessions, we build a metric that approximates the labor hours of editors in the encyclopedia. Using this metric, we first compare laborbased analyses with output-based analyses, finding that the activity of many editors can appear quite differently based on the kind of metric used. Second, we use edit session data to examine phenomena that cannot be adequately studied with purely output-based metrics, such as the total number of labor hours for the entire project.

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