Computational Literary Studies: Participant Forum Responses, Day 2


Katherine Bode

The opening statements were fairly critical of Da’s article, less so of CLS. To balance the scales, I want to suggest that Da’s idiosyncratic definition of CLS is partly a product of problematic divisions within digital literary studies.

Da omits what I’d call digital literary scholarship: philological, curatorial, and media archaeological approaches to digital collections and data. Researchers who pursue these approaches, far from reducing all digit(al)ized literature(s) to word counts, maintain––like Da––that analyses based purely or predominantly on such features tend to produce “conceptual fallacies from a literary, historical, or cultural-critical perspective” (p. 604). Omitting such research is part of the way in which Da operationalizes her critique of CLS: defining the field as research that focuses on word counts, then criticizing the field as limited because focused on word counts.

But Da’s perspective is mirrored by many of the researchers she cites. Ted Underwood, for instance, describes “otiose debates about corpus construction” as “well-intentioned red herrings” that detract attention from the proper focus of digital literary studies on statistical methods and inferences.[1] Da has been criticized for propagating a male-dominated version of CLS. But those who pursue the methods she criticizes are mostly men. By contrast, much digital literary scholarship is conducted by women and/or focused on marginalized literatures, peoples, or cultures. The tendency in CLS to privilege data modeling and analysis––and to minimize or dismiss the work of data construction and curation––is part of the culture that creates the male dominance of that field.

More broadly, both the focus on statistical modelling of word frequencies in found datasets, and the prominence accorded to such research in our discipline, puts literary studies out of step with digital research in other humanities fields. In digital history, for instance, researchers collaborate to construct rich datasets––for instance, of court proceedings (as in The Proceedings of the Old Bailey)[2] or social complexity (as reported in a recent Nature article)[3]––that can be used by multiple researchers, including for noncomputational analyses. Where such research is statistical, the methods are often simpler than machine learning models (for instance, trends over time; measures of relationships between select variables) because the questions are explicitly related to scale and the aggregation of well-defined scholarly phenomena, not to epistemologically-novel patterns discerned among thousands of variables.

Some things I want to know: Why is literary studies so hung up on (whether in favor of, or opposed to) this individualistic, masculinist mode of statistical criticism? Why is this focus allowed to marginalize earlier, and inhibit the development of new, large-scale, collaborative environments for both computational and noncomputational literary research? Why, in a field that is supposedly so attuned to identity and inequality, do we accept––and foreground––digital research that relies on platforms (Google Books, HathiTrust, EEBO, and others) that privilege dominant literatures and literary cultures? What would it take to bridge the scholarly and critical––the curatorial and statistical––dimensions of (digital) literary studies and what alternative, shared futures for our discipline could result?

KATHERINE BODE is associate professor of literary and textual studies at the Australian National University. Her latest book, A World of Fiction: Digital Collections and the Future of Literary History (2018), offers a new approach to literary research with mass-digitized collections, based on the theory and technology of the scholarly edition. Applying this model, Bode investigates a transnational collection of around 10,000 novels and novellas, discovered in digitized nineteenth-century Australian newspapers, to offer new insights into phenomena ranging from literary anonymity and fiction syndication to the emergence and intersections of national literary traditions.

[1]Ted Underwood, Distant Horizons: Digital Evidence and Literary Change (Chicago: Chicago University Press, 2019): 180; 176.

[2]Tim Hitchcock, Robert Shoemaker, Clive Emsley, Sharon Howard and Jamie McLaughlin, et al., The Proceedings of the Old Bailey,, version 8.0, March 2018).

[3]Harvey Whitehouse, Pieter François, Patrick E. Savage, Thomas E. Currie, Kevin C. Feeney, Enrico Cioni, Rosalind Purcell, et al., “Complex Societies Precede Moralizing Gods Throughout World History,” Nature March 20 (2019): 1.


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3 responses to “Computational Literary Studies: Participant Forum Responses, Day 2

  1. Pingback: Computational Literary Studies: A Critical Inquiry Online Forum | In the Moment

  2. Pingback: Computational Literary Studies: Participant Forum Responses, Day 3 | In the Moment

  3. Pingback: In the Moment – Colchester Maths Tutor

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