Enumeration: Translating Between Letter and Number
February 6, 2014
With the help of new computer technology, the landscape of literary study is in a state of exciting transformation. How can this massive amount of newfound numerical data be translated into valuable insight about literature? Professor Andrew Piper has accepted this challenge of translation; his lecture will delve into the rewards and restrictions of studying language through a computational lens.
A decorated scholar of the Romantic era and the histories of reading and the book, Piper has also explored data-mining computer programs to uncover over-arching trends and patterns of influence that connect multiple literary works. These patterns are often invisible until viewed through the lens of computation. For example, one of Piper’s recent projects made use of computer programs to map how the Confessions of St. Augustine is an ancestor to the “conversion experience” of the modern novel genre. For more on this project, visit Piper’s website >>.
In addition to being Associate Professor of German and European Literature and an associate member of the Department of Art History and Communication Studies at McGill University, Piper is also the author of Dreaming in Books: The Making of the Bibliographic Imagination in the Romantic Age (University of Chicago Press, 2009), a work which revisits the nineteenth century’s love affair with the codex, as well as exploring the future of our relationship to it in the digital age. Dreaming in Books was awarded the 2009 MLA Prize for a First Book. Piper’s second work, Book Was There: Reading in Electronic Times (University of Chicago Press, 2012), engages deeply with the entangled past and future of reading, and the extent to which new technologies will change the way we read. Publisher’s Weekly calls Book Was There “a fascinating glance at the page as it was, as it is, and as it might yet be.”
On January 15th, 2014, the international research team which Piper co-leads learned that it will receive a share of $5.1 million in funding as part of the Digging into Data Challenge, which addresses how computationally-based research methods are changing the face of research for the humanities and social sciences.