Last week was a big week: we finished Beloved, received assignments for our Voyant Tools presentations, and read through W.E.B. Dubois’s data portraits. From seeing the name of the Dubois book, I had actually been assuming these were contemporary data portraits generated from Dubois’s writing, given that this was a computational literary studies class; it was very impressive to read through the plates as what they actually were, knowing that they would have had to be done by hand without computational help. The exhibition, for all that it deserves critical examination, also enables us to critically examine our assumptions about the information-conveying bodies of the ‘past’ and the ‘present’, and where the line might be less clearly demarcated than we assume at first glance.
For the presentation, I got assigned the Summary, which I’m quite gratified by because I think it’s one of the more obviously interesting and productive tools that Voyant has. Having used it for personal investigations a few times before, I always found myself fascinated by the revelatory nature of the “Distinctive Words” function within a corpus, and am curious about whether that and some of the other summary functions would be conducive to an analysis of differing stylistics in parts 1, 2, and 3 of Beloved. (Distinctive words within my journal in 2020 as opposed to in 2018, 2019, and 2021: “vote,” “responsibility,” “pandemic,” “quarantine,” “sad,” and “biden.”)
Almost more so than distinctive words, I’m interested in things like sentence length and vocabulary density, which might be assumed to be more-or-less consistent across the same writer’s novel, but I’m curious as to whether this is true from Beloved because in many ways I think the three parts of the novel are to some degree generically and stylistically distinct. In doing an analysis like this, it’s also worth considering, of course, whether Voyant’s summary function biases the critic towards a search for difference over consistency, since it’s distance that it stresses through comparison, which could potentially lead to a critic’s overstatement of such differences.