Reading this article, particularly the part about sentiment analysis, was interesting to me because last year I did my thesis[1] regarding sentiment classification using a somewhat mixed approach (albeit pretty simple) where I factored in basic sentence structure in addition to word features to see improvement in accuracies. I found it really neat to see various cases where particular sentence structures like PRP RB VB DT NN would be much more likely to show up for a positive sentiment e.g. "I highly recommend this product" vs negative sentiment e.g. "They totally misrepresent this product"

I get the impression that while it is true the computational side of computational linguistics has seemingly seen more attention for lucrative reasons, but now it is seeing some success there more people trying to incorporate more from the linguistic side, when it doesn't cause for a huge amount of computational expense.

It doesn't seem like anything new, however, that business needs drive funding for particular areas in academia. Sadly, more so than ever considering the greed of the school systems (but that is another topic).

[1] https://digital.lib.washington.edu/researchworks/handle/1773...