I have spent a lot of time experimenting with and exploring topic models of text. Aside from an article, some blog posts, and a bunch of strongly held opinions, that time also produced quite a few lines of computer code for handling topic models from MALLET. I started out with a big file of R functions, then escalated to a folder full of R functions. The organization got ever more byzantine, even more so when I collaborated with others. Finally I bit the bullet and, following the gospel of Wickham, converted my pile o’ scripts into an R package, called dfrtopics because I was making models of data from JSTOR’s Data for Research. There it has sat, on github, accumulating bits now and then, plus some function documentation written in a fit of compulsion, but really not in a form that anyone but I could use (and, as time went on, becoming hard for me to use too). My website has had a note promising a tutorial demonstration of how to use my package for nigh-on two years, but no demonstration demonstrated itself.

The package was hard to use and document because of the messy and ad hoc way I represented pieces of the topic model. A hierarchical model is not easy to wrap your mind around, and different questions require different slices of the model to answer. And all the mess of code passing around random collections of data frames, lists, and who knows what else seemed like fertile ground for errors and glitches, even when the whole thing seemed more or less to do what I wanted most of the time.

So: in a questionable expenditure of energy, I’ve spent a few days applying some polish to the package. Herewith dfrtopics version 0.2. Install it from github with devtools::install_github("agoldst/dfrtopics").

Three things are new from a potential user’s perspective—and my hope is that the idea of a potential user is slightly less far-fetched than before. First, there is now an introductory tutorial in the form of a package vignette. Second, the whole package has been rewritten around the idea that a topic model is an object, stored in a single R variable. Third, I have tried to make everything as modular as possible, so that the usefulness of the package is not restricted to MALLET models of DfR data. If you have other textual data in wordcount-form—oh, let’s say, 180,000 18th-through-early-20th-century volumes—you might write up some variant file-loading code if necessary, then use the package functions to model those texts with MALLET. And if you have wordcount data that you want to analyze in R in some other way than with MALLET, there are still, I hope, some useful things here for converting those wordcounts into data frames or term-document matrices.

I am co-organizing a seminar on The Production of Modernist Disciplinarity at this November’s MSA in Boston with Jonathan Goodwin (University of Louisiana, Lafayette). As a supplement to the very terse description you can find on the site, here is a slightly longer one:

The Production of Modernist Disciplinarity

Recent modernist studies are characterized by the aspiration to expand geographically, chronologically, and across media. Yet the core of “modernism” as an aesthetic, a period, and a canon of writers and artists has proven strikingly stable. This seminar invites new approaches to studying modernist disciplinarity itself, including (but not limited to) quantitative approaches, like citation analysis and probabilistic modeling, that have recently been brought to bear on disciplinary history in the humanities. How can we understand (or change) the forces that either stabilize or disrupt scholarship on modernism?

This was meant to underline that though Jonathan and I are both interested in quantitative methods for understanding disciplinary continuity and change, this is not an exclusively quantitative or “digital” seminar. All approaches are welcome. Please don’t hesitate to write me (contact information at right) or Jonathan (joncgoodwin@gmail.com) if you have any questions.

Conference registration is open. Seminar registration officially closes tomorrow, September 1. The conference early-registration discount ends September 15.

Despite any rumors you may have heard to the contrary, our seminar will not be a Zimbardo-style experiment on the production of disciplinarity.

If we want to do sociology of literature, let’s get away from texts for a bit.

One of the most promising things about the current interest in quantitative methods for literary study is that it offers us some alternatives to reading as a method. There are important questions about literature—above all, about literature as a social and historical system—that cannot be answered with the tools of the expert textual interpreter. Such questions are better answered, I believe, in closer collaboration with our disciplinary kindred in the social sciences.

Thanks to a new special issue of Cultural Sociology focused on literature, we have a chance to look at some concerete examples of what sociological approaches to literary problems currently look like. In this post I’ll discuss the excellent essay there by Gisèle Sapiro, Translation and Symbolic Capital in the Era of Globalization: French Literature in the United States. Sapiro, whose work I have been following for a while, works in the tradition of the sociology of fields, and has written on both twentieth-century literary history and contemporary world literature. This latest essay is particularly fun to think with, because I have my greedy paws on some of the same data Sapiro uses, so it will be possible to look in some detail at the sort of evidence and the sort of analysis her approach entails—and, perhaps, to think how to extend it.

Here are some tentative notes on methodological problems in quantitative approaches to literary history that I’ve been worrying over. I’m moved to post these because of two great discussions of quantitative literary studies by sociologists, a review by Ben Merriman of recent work by Franco Moretti and Matt Jockers, and a blog post by Tressie McMillan Cottom on quantitative text analysis across the disciplines. Monomaniacal proselytizer for closer relations between sociology and literary study that I am, first I say: go read those! They’re really great! Also, I’m leaping onto this bandwagon. Mostly I want to indicate how this very useful pressure from sociologists might help literary scholarship to refine its methods and clarify its research program. I’m afraid this is all very drafty, in the form of broad assertions with basically no citations. Blogging!

In Easy Lecture Slides Made Difficult, I showed how to use markdown to make slides while still retaining some aesthetic flexibility. All that was required was a handful of TeX Macros, a little python script, a few Makefiles, and a maniacal commitment to automation. That was an enjoyable trip into the abyss, but what if your slides regularly include the results of calculations, data visualizations, or computational examples? Then it is time to, how do they say it these days, dive deeper. Thanks to R Markdown and knitr, it is possible to build on the pandoc/beamer system I described before to incorporate program code and its results. Call it, uh, Presentationally Literate Programming.

I am spurred to describe my approach by two things: first, I have had a whole semester of teaching Literary Data to work out the kinks; in that graduate course I regularly used R markdown-based slides to present new material. (Here are a couple examples: slides on network visualization, April 23, 2015; slides on topic modeling and PCA for literary texts, April 16, 2015.) Second, I was just at a conference where almost everyone’s presentation had slides with R output in them, but it seemed like people might…benefit…from an example showing how to make the aesthetics of the R output and the slides more consistent with one another. I’ll also show how the same R markdown can be the basis of slides, speaker notes, and a handout for audience members to take notes on. And I’ll show the settings for incorporating program code into the slides, which I used in my teaching. At the end of this post, I imagine you will question my sanity. The whole setup can be found in this repository subdirectory on github.

[Update, November 2015. I’ve made a slightly easier-to-use version of the same setup available as an R package here.]

I’m giving a talk at the Center for the Humanities at Temple tomorrow, Wednesday, April 8, in their Digital Humanities in Practice Series.

Quiet Transformations of Literary Study, 1889–2013

The history of literary scholarship is usually presented as a succession of conflicting ideas. Yet gradual, distributed change is equally significant, and often less visible to practitioners, who remember recent dramas better than the unspoken norms of eighty years ago. Understanding such change requires new methodologies. I present an analysis using probabilistic topic modeling to reveal broad trends in more than 21,000 literary-studies journal articles. As literary and cultural studies confronts the interpretive challenges posed by topic modeling and other quantitative methods, we increasingly enter the methodological domain of the social sciences.

It’s at 4:00 p.m. in the CHAT Lounge (details on the CHAT website). I can promise at least 300 words on tokenization¹ and the phrase “post-Marxist Mechanical Turk” used as sincere praise.

I don’t think any writer did more to form me than Terry Pratchett. That might be a bit of a dangerous thing for a professional literary scholar to say. It would be easier to recount how much Ulysses, say, meant to a budding adolescent highbrow. In fact, though, I suspect that as a teenager, and not only as a teenager, I had a Pratchettian reading of the novel: Joyce’s Dublin as Ankh-Morpork, puns and pastiche as the engine driving the narrative language forward, the library of culture as an interdimensional transit zone, and no icon left unsmashed. In any case, I’m certain I would be a very different person if my elementary-school librarian hadn’t read Truckers to us and started me on a Pratchett kick that never stopped.

I’ll be in Cambridge (in the Dave Barry sense of the word) on Wednesday, March 4, to give a talk to the British Studies Colloquium of the Harvard English department. Here’s my abstract:

The Modernist Period Concept: Threat or Menace?

The early twentieth century is the modernist period. Or so we say. Does this idea, codified in the institutions of modernist studies, limit our understanding of literary history? In this talk, I use a study of thousands of MLA Bibliography entries to argue that the modernist period concept is regulated, in practice, by an all-too-familiar canon of authors (Joyce, Eliot, Woolf, Pound), in spite of efforts to expand modernism culturally, geographically, and historically. These names stand for the equation of formal-aesthetic innovation, as it was practiced in Euro-American avant-garde scenes, with the literary culture of modernity. The menace of the modernist period concept is that this equation is tenacious but wrong. It conflates the whole of the literary field with its most consecrated part, precluding the study of the structural transformation of literary production and reception in the first half of the century. That transformation gives rise, not to a legible Zeitgeist, but to a system of hierarchically organized genres with non-synchronous histories. By way of speculative conclusion, I briefly compare histories of several popular fiction genres and suggest that the study of literary classification systems is a necessary complement to the study of that single high-literary genre we call “modernism.”

The talk is at 5:15 p.m. in Barker 114.

It has come to my attention that while I am quantifying literary studies in Boston, Franco Moretti will be giving the Goldstone lecture at NYU. If you are racing to my talk and tell your phone, “Take me to the Goldstone lecture, double-quick!” check that you are not being directed to New York City.

A new OS upgrade means new Java problems. I use MALLET, which depends on rJava, which depends on Java. Here’s what I did to get things working (apparently, for now).

Over the winter break came the terribly sad news of the sudden death of Daniel Albright. His own web site has a notice and a brief biography of this remarkable scholar and teacher; the Harvard Crimson also published an obituary. (If I find other notices and memorials I’ll edit this post.) I’m thinking of him and of all the people close to him.

He was my teacher for one semester in my last year as an undergraduate, when I took his seminar on Beckett and Auden (“Early Postmodernism”). I’m sorry to say I didn’t keep in touch after I graduated, but in thinking about Daniel Albright these last few weeks I’ve realized he made a big mark on me, which I wanted to briefly trace here by way of tribute.