As alluded to in the previous post, Ari and I have been hard at work at quantitatively analyzing how programming languages get adopted -- or fail to. For example, the above chart shows that for commercial projects, social factors (open source libraries, legacy code, and familiarity) matter much more than language support (correctness, simplicity, development speed, tools, language features, ...). This chart is also fascinating because we see that developers act differently depending on the company size.
Check out our draft "Social Influences on Language Adoption" for more fun charts where we performed and analyzed large surveys and also looked at 10 years of the SourceForge repository with over 200,000 projects. As another example, we validated some of our suspicions in the sociology survey that DSLs can be understood in terms of competing niches (e.g., popularity comes from spreading to other niches, not being the best in the niche). We'd love comments! More is in the pipeline -- we'll be releasing the raw data and also a small writeup about the methodological hazards we had to circumvent for this type of research.