It’s not very hard to get individual texts in digital form. But working with grad students in the humanities looking for large sets of texts to do analysis across, I find that larger corpora are so hodgepodge as to be almost completely unusable. For humanists and ordinary people to work with large textual collections, they need to be distributed in ways that are actually accessible, not just open access.

This article in the New Yorker about the end of genre prompts me to share a theory I’ve had for a year or so that models at Spotify, Netflix, etc, are most likely not just removing artificial silos that old media companies imposed on us, but actively destroying genre without much pushback. I’m curious what you think.

(This is a talk from a January 2019 panel at the annual meeting of the American Historical Association. You probably need to know, to read it, that the MLA conference was simultaneously taking place about 20 blocks north.)

Disciplinary lessons

Critical Inquiry has posted an article by Nan Da offering a critique of some subset of digital humanities that she calls “Computational Literary Studies,” or CLS. The premise of the article is to demonstrate the poverty of the field by showing that the new structure of CLS is easily dismantled by the master’s own tools. It appears to have succeeded enough at gaining attention that it clearly does some kind of work far outsize to the merits of the article itself.

I’ve gotten a couple e-mails this week from people asking advice about what sort of computers they should buy for digital humanities research. That makes me think there aren’t enough resources online for this, so I’m posting my general advice here. (For some solid other perspectives, see here). For keyword optimization I’m calling this post “digital humanities.” But, obviously, I really mean the subset that is humanities computing, what I tend to call humanities data analysis. [Edit: To be clear, ] Moreover, the guidelines here are specifically tailored for text analysis; if you are working with images, you’ll have somewhat different needs (in particular, you may need a better graphics card). If you do GIS, god help you. I don’t do any serious social network analysis, but I think the guidelines below should work relatively with Gephi.

Practically everyone in Digital Humanities has been posting increasingly epistemological reflections on Matt Jockers’ Syuzhet package since Annie Swafford posted a set of critiques of its assumptions. I’ve been drafting and redrafting one myself. One of the major reasons I haven’t is that the obligatory list of links keeps growing. Suffice it to say that this here is not a broad methodological disputation, but rather a single idea crystallized after reading Scott Enderle on “sine waves of sentiment.” I’ll say what this all means for the epistemology of the Digital Humanities in a different post, to the extent that that’s helpful.