Announcing gh-impact, a measure of influence among open source developers. This work is available at http://www.gh-impact.com.
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…)
- 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.