This is a follow-up to yesterday's post on discription. That’s a preliminary to today’s post, which is more generally about the possibilities for collaborative online learning in literary and cultural criticism. In particular, I want to stress the need to extend this learning beyond the academy and into the general public.
I've also taken my Language Log post on literary criticism and computational linguistics, added a conclusion and a postscript, and posted the entire document as a PDF to my SSRN page:
From the postscript:
I believe that the work currently being done in natural language processing (NLP) in literary studies will, in time, redeem the work that I did back in the 1970s and 1980s. That work is predicated on the idea of computation and the expression of that idea in the early cognitive sciences and in computational linguistics, in which I was instructed by David Hays.
Literary studies missed the boat on the so-called cognitive revolution and, despite the emergence of cognitive criticism in the middle and late 1990s, literary studies still hasn’t gotten the message. Briefly and crudely, the cognitive revolution is what happened when the idea of computation hit the human sciences. By the mid-1980s, however, the first wave of cognitivism had died down and newer work arose in which one could easily miss the importance of computation. That work – I’m thinking particularly of cognitive metaphor and conceptual blending, theory of mind, and mirror neurons – is what captured the attention of literary cognitivists and allowed them to go cognitive while not having to come to grips with computation.
That blissful ignorance may persist for another decade or two, but not much longer, for the implications of literary work based on the techniques of NLP will require critics to think about computation, not simply as a tool for crunching large piles of data, but as a process in the minds of readers and writers. … When those days come, people will have no choice but to think more deeply about the strange conceptual objects coughed up by these high tech picks and shovels. Investigators will find themselves inching inevitably toward a computational understanding of texts themselves, and of the minds of which those texts are evidence and from which they are products. When those days emerge investigators will find a rich and various literature awaiting their attention.
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