I’m waiting for one of my colleagues to lend me some books on bibliometrics. However, in the meantime, in my naïveté, I have created a metric[1].

My metric is not a terribly good one, though perhaps it is no worse than some other well-established ones. While it somewhat defensibly measures reach and productivity, my metric also fails on other fronts.

I’ve called my metric gh-index. It works on the same math as h-index, which is fairly widely known. I’ve translated the logic of h-index to evaluate GitHub stars. The (questionable) assumption is that GitHub stars are the open source software equivalent to academic citations.

It’s a comparison that is kind of interesting. To be clear, I’m not trying to make OSS contributions equivalent to academic citations.  But my rhetorical point is that is that GitHub stars and scholarly citations are both hard-earned recognition, even though they represent very different types of labor.

So, you can calculate the gh-index of any GitHub user here.  This web tool queries the GitHub API, and parses the resulting data to make gh-index calculations. Also, if you’re interested, you can see the code here.

[1] Here is an example of a much more well thought out analysis.

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