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Network analysis of the sourceforge community

Network analysis of the sourceforge community. By Chris Zachor. Overview. Introduction Background Open Source Software The SourceForge community and network Previous Work What can be done different? Related Work Conclusion Questions. Introduction.

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Network analysis of the sourceforge community

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  1. Network analysis of the sourceforge community By Chris Zachor

  2. Overview • Introduction • Background • Open Source Software • The SourceForge community and network • Previous Work • What can be done different? • Related Work • Conclusion • Questions

  3. Introduction • Goal: Use network analysis to better understand the SourceForge community developers • Identify key developers and groups of developers who create popular open source applications

  4. Open Source Software • Open Source (OS) Software continues to be a popular alternative to standard commercial software • Many OS alternatives to traditional closed source projects exist • osalt.com provides a convenient database for this

  5. The SourceForge Community • A website to help promote collaboration between developers of OS projects • A repository for OS projects • Developers: revision control, bug tracking, donation system, etc. • Users: bug reporting, recommendations, commenting, etc.

  6. The SourceForge Network • Multiple networks can be formed from the SourceForge community • Project-Developer network • Developer network • Project network • Lots of interesting data to be collected from the website such as total downloads of a project, length of developer membership, recommendations, etc.

  7. Project-Developer Network • A bipartite graph with two groups of vertices: projects and developers • An edge indicates the developer works on that project

  8. Developer Network • A collaboration network • Edges are formed where one developer 1 has worked with developer 2

  9. Project Network • An edge can represent a related project • An edge can represent projects that share a developer • Or perhaps an edge can represent a related project

  10. Previous Work on SourceForge • The open source group at Notre Dame • Used network analysis as a tool to understand the Open Source Software phenomenon and predict growth over time • Monthly data dumps directly from SourceForge.net

  11. What Can Be Done Different? • The latest paper produced concerning network analysis was in 2007 • The project count has more than doubled in size to ~250,000 projects (from ~90,000 in 2007).

  12. What Can Be Done Different? • Their main concern was with how the network was evolving • Focus was on the change in measures from month to month • No interpretation of data

  13. Related Work • M. E. J. Newman • Scientific Collaboration Networks • 4 Major Databases spanning 5 years • Collaboration network using authors who have worked together on a single paper • Explored what fields were producing more papers, what fields collaborated more, etc.

  14. Related Work • Obermeieret al. • University College Dublin • Co-authorship between departments at UCD • They wanted to understand the interdisciplinary publication culture within the University • Looked at brokerage individuals and how they play a part in their own departments • Found these brokerage individuals to be most central within their own departments

  15. Related Work • Gao and Madey • Network analysis of SourceForge • Used as a tool to understand the open source movement • Documented the growth of the SourceForge community • Structural analysis, centrality analysis, path analysis • They did not interpret the data

  16. Related Work • Xu, Christley, and Mady • Network analysis of the SourceForge community • Attempt to explain the success and efficiency of OS development practices • Noted that the SourceForge Network is a scale free network • Also noted the presence of the small world phenomenon within the community

  17. Related Work • Xu, Christy, and Madey continued • Observed that co-developers and active users were a major factor in large scale projects • Meanwhile, project leads and core developers were largely involved in small projects

  18. Conclusion • While previous studies were focused on growth and why the process is a success, this study will focus on how key developers and groups play a part in creating popular software • Many attributes not looked at in previous studies

  19. Questions? Anyone?

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