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Author here. You are absolutely right. As I mentioned in the notes, I think this matters a bit less than it might seem like (the stationary distribution does no

Author here. You are absolutely right. As I mentioned in the notes, I think this matters a bit less than it might seem like (the stationary distribution does not change if you add a diagonal matrix) but clearly some languages will have a higher propensity for people to stay. I think this flaw is even smaller than the issue of using Google statistics to infer transition probabilities. It's just a shitty proxy, at best. At the end of the day, there's a lot of assumptions going into this analysis. I hope I didn't make it seem more serious than I meant it to be – it's really just a fun project and kind of a joke not to meant taken seriously. That being said, I think the conclusions are at least "directionally" correct. They might be off by a factor of 2x or 5x or even 10x, but the stationary distribution exhibits an even bigger spread (multiple orders of magnitude) so I suspect the final ranking is still "roughly" correct (with a very liberal definition of "rough")

j2kun 10y ago
The thing I like most about this post is that it's falsifiable. We will know in ten years whether C and Java are still popular, and whether Go succeeds in the sense this data suggests. So thank you for being concrete and clear, even if it's all in fun and other people don't like it :)
- erikbern 10y ago
  This is a great point. It's a model that predicts something about the future. I could have backtested it on historical Google stats to figure out if it's a good model :)
  - j2kun 10y ago
    In an unrelated note: interested in doing a guest post over at Math ∩ Programming? I see you've got lots of cool stuff with high-dimensional NN :)
- thaumasiotes 10y ago
  > whether Go succeeds in the sense this data suggests An interesting thing about this methodology is that it is extremely sensitive to the age of a language. It's possible to switch from an old language to a new language, but not the other way around -- so if you happen to do your measurements after a language has had some uptake but before it's been around for long enough that people have built significant projects on it and subsequently gotten sick of it, the future distribution by this method can only be 100% New Language. (Because sometimes people switch to New Language, but no one ever switches away.) Actually, to predict the future distribution of language use, you also need to know the rate of people moving from nothing ("I just had a brilliant idea!") to each language. If everyone eventually transitions to Go, but everyone starts in Ruby, then the division of market share between Go and Ruby depends in part on how frequently people start new projects.
  - j2kun 10y ago
    I didn't interpret the results in this post as "predicting the future distribution of language use." Rather, I interpreted the ranking as an indicator of a qualitative trend in that distribution. I think the author also made this very clear. And of course, all things trend toward newness, so your objection there seems more about time or human psychology than the methodology of the post.
    - thaumasiotes 10y ago
      From the post: > I took the stochastic matrix sorted by the future popularity of the language (as predicted by the first eigenvector). Emphasis in original.
      - j2kun 10y ago
        Nevertheless, it seems quite obvious the author did not literally interpret the eigenvector as "x% of future projects will be written in Go." Rather, the conclusions he drew were along the lines of "Oh wow look Go is on top, C and Java are still relevant."
pmarreck 10y ago
And I share my Go reservations with you, given the whole error-handling (or lack thereof) philosophy as well as information emerging that it may require 100 lines of Go to do roughly the same amount of work as 20 lines of Elixir or Haskell, according to one example at https://medium.com/unbabel-dev/a-tale-of-three-kings-e0be17a16e2b#.48qomfq30 https://medium.com/unbabel-dev/a-tale-of-three-kings-e0be17a... (Although I concluded the Haskell-Elixir equivalency myself based on functional semantics)
- psiclops 10y ago
  Go is verbose. There is a lot of thought behind that, but that is an intentional design aspect of the language. Personally I would not use gin, either net/http, gorilla/mux, or httprouter are solid choices
  - pmarreck 10y ago
    What is the empirically-determined advantage of verbosity, then?
    - psiclops 10y ago
      A lot of it boils down to making it easier for developers to work with each other, rather than any technological benefit. The less magic that happens and the more code that is commonly used by all developers, the easier it is for others to read your code and understand what it does. Rob Pike and others have some interesting talks and blog posts on this
omaranto 10y ago
That bit about the stationary distribution not changing if you add a diagonal matrix sounds completely wrong to me. Let me see if I understand what you mean. Given a matrix M with non-negative entries (and no row of just zeros), let S(M) denote the stochastic matrix you get by normalizing each row of M. You are saying that if M is any matrix and D is a diagonal matrix with non-negative entries then S(M) and S(M+D) have the same stationary distribution?
- MrQuincle 10y ago
  Moreover data is collected over the entire history. A matrix is a linear operator from time step T_i to T_i+1. By conflating all historical observations into one matrix it definitely is not an ordinary transition matrix. That apart from the fact that it is questionable that it can be represented by an operator that is finite and linear. It's more likely a stochastic process (infinite matrix) with births and deaths. I would be surprised if it became true. :-)
  - foobun 10y ago
    That was my immediate thought upon reading. A little more accuracy in the description would be helpful. This should be presented as: "If this aggregated data reflected a constant across time, then we can see where language usage would end up in the 'long run distribution'." But the jump matrix shown here will change with time. Most likely, if search results could be binned up by time period, the time dependence of the distribution represented by the eigenvector(s) would be somewhat interesting to watch, even if not remotely predictive. Could animate that or contour plot it.... exercise for the author... :)
- erikbern 10y ago
  Right. Both the matrix S and the identity matrix will project the stationary distribution onto itself. So any linear combination of them will project the stationary distribution onto itself. Let me know if I'm saying something really stupid
  - omaranto 10y ago
jabot 10y ago
Another thing which seems at least as important: How many projects are _started_ in a language, and how many _die_? Given p.e. Java - It may seem that there is a huge flow to go. However, if there are enough new projects started in java, then the number of java projects might still rise faster than the number of go projects.

j2kun 10y ago

The thing I like most about this post is that it's falsifiable. We will know in ten years whether C and Java are still popular, and whether Go succeeds in the sense this data suggests. So thank you for being concrete and clear, even if it's all in fun and other people don't like it :)

erikbern 10y ago
This is a great point. It's a model that predicts something about the future. I could have backtested it on historical Google stats to figure out if it's a good model :)
- j2kun 10y ago
  In an unrelated note: interested in doing a guest post over at Math ∩ Programming? I see you've got lots of cool stuff with high-dimensional NN :)
thaumasiotes 10y ago
> whether Go succeeds in the sense this data suggests An interesting thing about this methodology is that it is extremely sensitive to the age of a language. It's possible to switch from an old language to a new language, but not the other way around -- so if you happen to do your measurements after a language has had some uptake but before it's been around for long enough that people have built significant projects on it and subsequently gotten sick of it, the future distribution by this method can only be 100% New Language. (Because sometimes people switch to New Language, but no one ever switches away.) Actually, to predict the future distribution of language use, you also need to know the rate of people moving from nothing ("I just had a brilliant idea!") to each language. If everyone eventually transitions to Go, but everyone starts in Ruby, then the division of market share between Go and Ruby depends in part on how frequently people start new projects.
- j2kun 10y ago
  I didn't interpret the results in this post as "predicting the future distribution of language use." Rather, I interpreted the ranking as an indicator of a qualitative trend in that distribution. I think the author also made this very clear. And of course, all things trend toward newness, so your objection there seems more about time or human psychology than the methodology of the post.
  - thaumasiotes 10y ago
    From the post: > I took the stochastic matrix sorted by the future popularity of the language (as predicted by the first eigenvector). Emphasis in original.
    - j2kun 10y ago
      Nevertheless, it seems quite obvious the author did not literally interpret the eigenvector as "x% of future projects will be written in Go." Rather, the conclusions he drew were along the lines of "Oh wow look Go is on top, C and Java are still relevant."

pmarreck 10y ago

And I share my Go reservations with you, given the whole error-handling (or lack thereof) philosophy as well as information emerging that it may require 100 lines of Go to do roughly the same amount of work as 20 lines of Elixir or Haskell, according to one example at https://medium.com/unbabel-dev/a-tale-of-three-kings-e0be17a16e2b#.48qomfq30 https://medium.com/unbabel-dev/a-tale-of-three-kings-e0be17a... (Although I concluded the Haskell-Elixir equivalency myself based on functional semantics)

psiclops 10y ago
Go is verbose. There is a lot of thought behind that, but that is an intentional design aspect of the language. Personally I would not use gin, either net/http, gorilla/mux, or httprouter are solid choices
- pmarreck 10y ago
  What is the empirically-determined advantage of verbosity, then?
  - psiclops 10y ago
    A lot of it boils down to making it easier for developers to work with each other, rather than any technological benefit. The less magic that happens and the more code that is commonly used by all developers, the easier it is for others to read your code and understand what it does. Rob Pike and others have some interesting talks and blog posts on this

omaranto 10y ago

That bit about the stationary distribution not changing if you add a diagonal matrix sounds completely wrong to me. Let me see if I understand what you mean. Given a matrix M with non-negative entries (and no row of just zeros), let S(M) denote the stochastic matrix you get by normalizing each row of M. You are saying that if M is any matrix and D is a diagonal matrix with non-negative entries then S(M) and S(M+D) have the same stationary distribution?

MrQuincle 10y ago
Moreover data is collected over the entire history. A matrix is a linear operator from time step T_i to T_i+1. By conflating all historical observations into one matrix it definitely is not an ordinary transition matrix. That apart from the fact that it is questionable that it can be represented by an operator that is finite and linear. It's more likely a stochastic process (infinite matrix) with births and deaths. I would be surprised if it became true. :-)
- foobun 10y ago
  That was my immediate thought upon reading. A little more accuracy in the description would be helpful. This should be presented as: "If this aggregated data reflected a constant across time, then we can see where language usage would end up in the 'long run distribution'." But the jump matrix shown here will change with time. Most likely, if search results could be binned up by time period, the time dependence of the distribution represented by the eigenvector(s) would be somewhat interesting to watch, even if not remotely predictive. Could animate that or contour plot it.... exercise for the author... :)
erikbern 10y ago
Right. Both the matrix S and the identity matrix will project the stationary distribution onto itself. So any linear combination of them will project the stationary distribution onto itself. Let me know if I'm saying something really stupid
- omaranto 10y ago

jabot 10y ago

Another thing which seems at least as important: How many projects are _started_ in a language, and how many _die_? Given p.e. Java - It may seem that there is a huge flow to go. However, if there are enough new projects started in java, then the number of java projects might still rise faster than the number of go projects.