· 2012
Social coding in GitHub
- 984citations
- 2012year
Short summary
GitHub users make rich social inferences from networked activity data, enabling better collaboration, skill development, and reputation management in large-scale distributed projects.
AI-generated from the title and abstract; the full text is not read.
Key points
- GitHub users infer social information, such as technical goals and project viability, from networked activity data.
- These inferences are combined into strategies for work coordination, skill advancement, and reputation management.
- Transparency in social coding platforms can significantly improve large-scale distributed collaborations and learning.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source., 2012 · DOI ↗
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Field: Computer Science Applications
Computer Science ApplicationsComputer Science