Why Digital Humanists don't need to understand algorithms, but do need to understand transformations

Debates in the Digital Humanities 2016 is now online, and includes my contribution, "Do Digital Humanists Need to Understand Algorithms?" (As well as a pretty snazzy cover image…) In it I lay out distinction between transformations, which are about states of texts, and algorithms, which are about processes. Put briefly:

Put simply: digital humanists do not need to understand algorithms at all. They do need, however, to understand the transformations that algorithms attempt to bring about. If we do so, our practice will be more effective and more likely to be truly original.

It then moves into one case study; the Jockers-Swafford debate of 2015, large parts of which hung on whether the Fourier transform was a black box and how it its use as a smoothing device might be understood. It's like a lot of what's on this blog, only better thought and edited.

The transformation/algorithm distinction is not a completely firm one, but I have found it extremely useful in a lot of research and teaching problems I've approached over the last year. So in addition to advertising that article for your consumption/fall syllabi production, I wanted to take the occasion to put on github a tiny little germ of a project to provide one-page, transformation-oriented introductions to basic text-analysis concepts that came out of using this thinking for a workshop on text analysis at the NIH in Bethesda, and describe what's in it. I'd love for anyone else to use it, fork it, whatever.

Plot arceology 2016: emotion and tension

Some scientists came up with a list of the 6 core story types. On the surface, this is extremely similar to Matt Jockers's work from last year. Like Jockers, they use a method for disentangling plots that is based on sentiment analysis, justify it mostly with reference to Kurt Vonnegut, and choose a method for extracting ur-shapes that naturally but opaquely produces harmonic-shaped curves. (Jockers using the Fourier transform, and the authors here use SVD.) I started writing up some thoughts on this two weeks ago, stopped, and then got a media inquiry about the paper so thought I'd post my concerns here. These sort of ramp up from the basic but important (only about 40% of the texts they are using are actually fictional stories) to the big one that ties back into Jockers's original work; why use sentiment analysis at all? This leads back into a sort of defense of my method of topic trajectories for describing plots and some bigger requests for others working in the field.

Nature publishes flat-earth research paper

I usually keep my mouth shut in the face of the many hilarious errors that crop up in the burgeoning world of datasets for cultural analytics, but this one is too good to pass up. Nature has just published a dataset description paper that appears to devote several paragraphs to describing "center of population" calculations made on the basis of a flat earth.