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Comment by justboxing | Hacker News Reader

It looks like a simple count of the language(s) detected by the linguist project -- https://github.com/github/linguist

Agreed, does not make much sense if it isn't a weighted average. A simple count could very well be littered with Hello-world repos (I've found a lot of those, in various languages) by people who are 'trying' github on.

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Good idea, maybe something like the number of code lines. That would value bigger projects higher then small projects. Which actually make sense to me. Because small projects are probably written in a specific language for a reason: batch files, css, html, examples, tests. Whereas I am interested in what language people choose for bigger projects, where several languages could used but still one has to be chosen.

It would also make sense to weight in the date a project started. Newer (big) projects would then weight higher then older (big) projects.

So I think taking in account the number of lines and age together is a good way to really visualize trends.

The problem is that one language might require less lines of code to achieve something of the same size/complexity of another language, if it's terser.

This would inflate the popularity of a language in proportion to its verbosity, but that could be approximately normalized by using line count ratios from the Great Language Shootout, which explicitly tracks how many lines various languages use to solve the same problem. Precision is pointless--the line ratios vary from problem to problem--but a rough approximation would be useful as long as you could get the statistics with and without it.

I think number of contributors would be a good metric, even though it penalizes lone projects, but I suspect that would be relatively even across languages compared to other metrics. For example, LoC is proportional to verbosity. Commit count is emphasizes languages that tend to have more bugs.

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