Announcing gh-impact, a measure of influence among open source developers. This work is available at

gh-impact measures open source influence. gh-impact is based upon the stars a project receives: an account has a gh-impact score of n if they have n projects with n stars. Higher gh-impact scores correspond to accounts that have many well-used projects. For more detailed information, see our reports.

Getting Meta about the Project

I’ve been growing as a scientist through all this, and I think this is probably my best work yet. From a project perspective, gh-impact features:

  • data processing pipeline (Postgres)
  • statistics pipeline (R, RStudio, knitr)
  • python data warehousing backend (Python, Flask-Diamond)
  • authoring pipeline (LaTeX)
  • open data sharing pipeline (JSON, Python)
  • public website (Jekyll, HTML, JS, jQuery, XML, CSS, etc…)
  • online search interface (Javascript, JSON, Python)
  • review of literature and industry (Zotero, arXiv, Google Scholar)
  • descriptive analysis (R)
  • introduction video/presentation (Keynote, YouTube)
  • “work in progress” article (R, LaTeX)

Makefiles everywhere. I’m pretty happy with it. We’re not done yet, though. I can see a few ways to gather more complete data and I have a ton of unanswered questions that I’m eager to investigate.