The difficulties engendered by the complicated patterns of repetition in Gertrude Stein’s 900-page novel _The Making of Americans_ make it almost impossible to read this modernist tome in a traditional, linear manner as any page (most are startlingly similar) will show. However, by visualizing certain of its patterns–by looking at the text “from a distance”–through textual analytics and visualizations, one can read the novel in ways formerly impossible and re-evaluate whether there is or is not “a there there.” This talk will focus on how various analytic methods (such as text mining and frequent pattern recognition) and visualization tools (such as FeatureLens and Spotfire) under research in the MONK project have been used to achieve a new *non*-reading of the text which Stein called her “masterpiece” and critiques called “linguistic murder.”
Helming from the English Department Tanya Clement’s dissertation, The Making of Digital Modernism: Re-reading Modernist Texts with Computer-Assisted Analysis, is genuinely groundbreaking and will contribute new readings and new knowledge to the scholarship on Gertrude Stein as well as a lesser-known figure, the Baroness Elsa von Freytag-Loringhoven (who was pivotal in the American Dadaist movement). By using a wide range of computational tools and techniques, ranging from text encoding to text mining and visualization, Clement’s project is a bracing demonstration of just how completely our readings and understandings of complex literary work can be reconfigured with the intervention of new media.
A continuously updated schedule of talks is also available on the Digital Dialogues webpage.
Unable to attend the events in person? Archived podcasts can be found on the MITH website, and you can follow our Digital Dialogues Twitter account @digdialog as well as the Twitter hashtag #mithdd to keep up with live tweets from our sessions. Viewers can watch the live stream as well.
All talks free and open to the public. Attendees are welcome to bring their own lunches.
Contact: MITH (mith.umd.edu, mith@umd.edu, 301.405.8927).