15-20 Minute Paper
Adam Hammond
Postdoctoral Fellow
University of Victoria, Department of English
Biography
Adam Hammond is a SSHRC postdoctoral fellow in the English Department at the University of Victoria, and teaches “The Digital Text” at the University of Toronto. His work focuses on literary modernism—particularly the work of T. S. Eliot, Virginia Woolf, and Wyndham Lewis—genre, narratology, the politics of style, and literature in the digital age.
Abstract
My talk argues that the future of digital literary analysis lies not in solving apparent interpretive cruxes, but rather (if you will forgive the awkwardness of the construction) in exploring the cruxishness of these cruxes. It’s about using digital resources to “problematize” literature—or simply to elucidate (qualitatively and quantitatively) how problematic it already is.
My talk will begin with some familiar statements about the perceived cultural split between humanities approaches (which value problems, cruxes, irresolvable quandaries) and scientific approaches (which seek solution, resolution, and definite answers).
I’ll next focus on two projects I’m currently leading, both of which are aimed at demonstrating the “problematic” nature of particular modernist literary texts—and also in engaging reading in the active exploration of their mysteries. The first is He Do the Police in Different Voices (hedothepolice.org), a website I developed collaboratively with Computational Linguist Julian Brooke and the 200 students of the Fall 2011 section of “The Digital Text,” the course I teach at the University of Toronto. The site provides users with resources for exploring the “dialogism” or multi- voicedness of T. S. Eliot’s The Waste Land, the working title for which was “He Do the Police in Different Voices.”
I will next look at The Brown Stocking, an ongoing project I am producing with Julian and the 320 students enrolled in this year’s sections of “The Digital Text.” The aim of this project is to develop a quantitative measure for describing novelistic “dialogism.” Its starting point is a richly-annotated TEI edition of Virginia Woolf ’s To the Lighthouse, tagged by my students for direct, indirect, and free indirect discourse. The aim of this project is to see whether, by using techniques of machine learning, we can develop an algorithm that can automatically detect free indirect discourse—instances where it simply doesn’t know who is speaking. We’re interested in seeing if we can teach an algorithm to behave like a reader of modernist literature, and learn to accept uncertainty.
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