Social coding in GitHub

TitleSocial coding in GitHub
Publication TypeConference Paper
Year of Publication2012
AuthorsDabbish, L, Stuart, C, Tsay, J, Herbsleb, J
Refereed DesignationRefereed
Tertiary AuthorsPoltrock, S, Simone, C, Grudin, J, Mark, G, Riedl, J
Secondary TitleProceedings of the ACM 2012 conference on Computer Supported Cooperative Work - CSCW '12
PublisherACM Press
Place PublishedSeattle, Washington, USA
ISBN Number9781450310864

Social applications on the web let users track and follow the activities of a large number of others regardless of location or affiliation. There is a potential for this transparency to radically improve collaboration and learning in complex knowledge-based activities. Based on a series of in-depth interviews with central and peripheral GitHub users, we examined the value of transparency for large-scale distributed collaborations and communities of practice. We find that people make a surprisingly rich set of social inferences from the networked activity information in GitHub, such as inferring someone else's technical goals and vision when they edit code, or guessing which of several similar projects has the best chance of thriving in the long term. Users combine these inferences into effective strategies for coordinating work, advancing technical skills and managing their reputation.

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