Monday, February 18, 2:00-3:00 pm
Williams Building 454
Introduction to Topic Modeling
This session will introduce an emerging method of textual analysis called topic modeling. Topic modeling identifies statistically-related clusters of words within any large corpus of digitized texts. Previously limited to intensive statistical programming and command line functions, topic modeling is becoming more accessible as well as increasingly conspicuous within the digital humanities community. We will consider an introduction to topic modeling, some applications of topic modeling with different archives (including the entire run of a scholarly journal and a historical archive of civil war-era Richmond newspapers), and try out a GUI version of the software package MALLET. Attendees are strongly encouraged to read the following:
- Jockers, Matthew. “The LDA Buffet Is Now Open; or, Latent Dirichlet Allocation for English Majors.” Matthew J. Jockers 29 Sep. 2011. Web. http://www.matthewjockers.net/2011/09/29/the-lda-buffet-is-now-open-or-latent-dirichlet-allocation-for-english-majors/
- Underwood, Ted, and Andrew Goldstone. “What Can Topic Models of PMLA Teach Us About the History of Literary Scholarship?” The Stone and the Shell. 14 Dec. 2012. Web. http://tedunderwood.com/2012/12/14/what-can-topic-models-of-pmla-teach-us-about-the-history-of-literary-scholarship/
- Nelson, Robert K. “Introduction.” Mining the Dispatch 2011-. Web. http://dsl.richmond.edu/dispatch/pages/intro
- Ratliff, Clancy. “Initial Foray into Topic Modeling for Rhetoric and Composition.” CultureCat 12 Feb. 2013. Web. http://culturecat.net/node/1564
Looking for more? Try out this useful sectional guide: Weingart, Scott. “Topic Modeling for Humanists: A Guided Tour.” the scottbot irregular 25 Jul. 2012. Web. http://www.scottbot.net/HIAL/?p=19113
