I doubt we can conclude much about programmers of a certain ilk as a result of the last 150 programming related updates on Twitter. Maybe if the data were more

I doubt we can conclude much about programmers of a certain ilk as a result of the last 150 programming related updates on Twitter. Maybe if the data were more transparent I could understand better what Delores Labs' graph represents. One problem I see in the methodology is that the sample size for each language would vary dramatically. So the results for e.g. Haskell is probably based on a relatively small number of tweets compared to e.g. Java where we would expect a lot more tweeting. The problem that introduces is that we base conclusions on maybe 1 or 2 individuals in the case of Haskell versus ~dozens who would have tweeted about Java. In the end, what difference does it make what some random people judge the sentiment of a tweet to be? Is the aggregate written sentiment of a language a scalar that strongly correlates to another scalar called happiness?