Digital Humanities

Literary Data graduate course

In Spring 2015 I offered a graduate course, Literary Data: Some Approaches (English 350:509). The course combined a discussion of theories of literary data from the mid-twentieth century to the present with an introduction to literary data analysis in R. The technical material, including slides and problem sets, continues to be available on the course website. I draw some lessons from the course in a Debates in the Digital Humanities 2019 essay, “Teaching Quantitative Methods: What Makes It Hard (in Literary Studies)” (preprint).

Data and Culture undergraduate course

In Fall 2022 I co-taught a general-audience undergraduate course, Data and Culture, with Meredith McGill. Many of the course materials, including lab exercises and slides, are available on the course site; the datasets from the course are distributed as an R package.

Using topic models for disciplinary history

I am interested in applications of probabilistic topic modeling, and have worked particularly on the language of scholarly journals. This work has branched into several projects:

“The Quiet Transformations of Literary Studies”

My article co-authored with Ted Underwood in New Literary History, “The Quiet Transformations of Literary Studies: What Thirteen Thousand Scholars Could Tell Us” (also available in preprint), argues that topic-modeling a century’s worth of journal articles suggests surprising long-term continuities and transformations in the history of literary scholarship.

The topic model we discuss most extensively can also be explored interactively in a website we created: Quiet Transformations.


As Signs Digital Humanities Fellow for 2014, I collaborated with the journal on their digital fortieth anniversary issue, Signs@40: Feminist Scholarship through Four Decades. This website includes an interactive visualization of a topic model of the journal (which I developed in collaboration with Andrew Mazzaschi, Susana Galán, C. Laura Lovin, and Lindsey Whitmore, building on my dfr-browser project), together with a set of commentaries on the model by feminist scholars.

dfrtopics: Create and Explore Topic Models in R

I developed an R package, dfrtopics, which helps with creating, exploring, and analyzing topic models within R. The package uses MALLET to build the models. It was initially specialized to JSTOR Data for Research data (hence the “dfr” in the name), but it can be used with other data sources, like feature counts from HathiTrust. For instructions on installing dfrtopics see the github project page; for an introduction to using the package, see the package vignette.

dfr-browser: Explore Topic Models in the Web Browser

I have also written a JavaScript/D3.js-based topic model explorer that runs in a web browser. This software is used for the Quiet Transformations browser and the Signs@40 site.

All source is available on github; that project page also explains how to set up the browser with new topic model data (which is easiest in conjunction with dfrtopics).

Resources for digital documents

I am interested in, not to say fanatical about, digital document preparation and typography. I describe the programs and formats I use, and why, in my page on LaTeX, markdown, and digital documents. Also available here are my brief introduction to markdown and an explanation of PDF for students.

Blogging on digitally humanistic topics

For all my blog posts related to the digital humanities, see under DH in the blog archive.