Description: In the last twenty years, English has become a data-rich field. With so much of the English-language print record digitized and at our scholarly fingertips---and with computer scientists daily claiming more sophistication for their techniques of handling it---the possibilities seem enormous for a radically expansive literary studies. Or they seemed so, but big literary data has not brought about the scholarly millennium some digital humanists hoped for. Why not? Is there hope, if not for a millennium, then at least for intellectual progress? I take case studies from my research modeling the history of literature scholarship and from teaching cultural data analysis to illustrate the potential, but also the limitations, of computational literary study. I argue that learning how to make data fit for purpose is the major methodological and pedagogical challenge for computational literary study today.


Bio: Andrew Goldstone is an associate professor of English at Rutgers University, New Brunswick. He works on twentieth-century literature in English, with a focus on sociological approaches. He is the author of Fictions of Autonomy: Modernism from Wilde to de Man (Oxford University Press, 2013). He has published on computational literary studies in New Literary History, CA: Journal of Cultural Analytics, and Debates in the Digital Humanities and developed software tools for exploring topic models of text. He is working on a history of genre fiction; part of this work in progress appears in the most recent issue of Book History. His website is andrewgoldstone.com.