[Edit: A lightly revised version of this post has been included in the Digital Humanities and Its Methods section of Debates in the Digital Humanities 2016, the first annual edition of a “book-length publication highlighting the particular debates that have shaped the discipline in a given year,” edited by Lauren F. Klein and Matthew K. Gold and published by the University of Minnesota Press.]
Before the spring semester starts, I wanted to share my digital humanities graduate syllabus from last fall and to share a few reflections about the experience. In planning the syllabus, I had useful conversations with Matt Wilkens, Andrew Goldstone, and Chris Forster, and I perused syllabuses generously posted online by Alan Liu, Rita Raley, Miriam Posner, and Lauren F. Klein. Sharing my syllabus in turn, then, seems only appropriate: Selisker DH Syllabus.pdf
The course is an introduction to the variety of methods and questions in digital humanities, leaning heavily toward applications for, and research questions in, literary studies. (A more general DH grad curriculum is also in the works at Arizona, about which more in the coming year.) I had students with backgrounds in literature, library science, gender studies, and creative writing, so I did what I could to emphasize questions that had implications for other disciplines, too.
Tools Looking for Research Questions
As I designed and taught the course, I came to think more and more that what distinguishes “mature” digital-methods work is its ability to connect digitally obtained evidence with other forms of evidence, and to integrate digital work into the research questions other scholars are asking. I believe one of my students was the source of a phrase that came up several times in our classroom as we moved from week to week: “Is this a tool in search of a research question?” It seemed to all of us that a tool in the service of a research question almost always led to the more exciting discussions.
I came up with a list of research focuses where the integration of digital tools was seeing particular success or seemed particularly promising beyond the archival, bibliographic, and textual studies with which humanities computing began. Weeks after I compiled my personal list—new sociologies of literature and culture, media theory and history, and science and technology studies—I saw that it had already been compiled (or strongly implied) in Alan Liu’s expanded version of “Where is the Cultural Criticism in the Digital Humanities?” in Debates in the Digital Humanities, about which I’ll have more to say in the conclusion. In a way the course was explicitly “about” connecting digital methods to contemporary research questions, though as an introduction to a very wide array of methods, there was also something of a “bus tour” element to the course design. The experience led me to conceive of the “advanced” DH courses, which I’ll design and teach in the future, as integrating a few digital methods tightly with a thematic and period focus. The first of these I’ve planned out might be called “Social Networks and Information Culture.” (In this regard, though, it seems to me that Lauren Klein’s and Andrew Goldstone’s courses, built in different ways around the theme of “data,” manage this thematic focus and the breadth of an introductory survey.) But before moving on from this introductory course, I’ll note some of the unexpected advantages of our sort of “bus tour” of digital humanities methods.
How Much Programming?
The DH syllabuses I have seen seem to vary most widely in their approach to the amount of technical skills they intend to teach. My own initial model was like that of the THATCamp workshop: in the second half of each week’s seminar, we’d go to the computer lab and get started using a new tool. I’d initially envisioned more guided instruction on programming basics, but the wide range of students’ abilities made this approach less practical than simply giving individual guidance to each of the thirteen students as needed. I think an excellent course could be built around Python or R (and has! see Matt Wilkens’s and Andrew Goldstone’s syllabuses), but I decided to err on the side of shallowness and breadth, making each lab a sort of hands-on session for a technique we’d seen used in a reading. In the first couple of lab sessions, for instance, we set up basic Wordpress or Drupal installations in order to see how database-driven websites work, an activity that set us up to talk about online archives and questions about databases. In another lab, we walked through the process of downloading and visualizing our social networks from Facebook or Twitter. In others, we tried out topic modeling, other distant reading techniques, and so on. On the negative side here, we were never able to go into much depth in the lab, but on the positive side, we got to work hands-on, at least a little, with most of the techniques we read about. While most of the guided work tended toward very modest goals, the independent project work time in the last five or six weeks seemed much more successful. There, students went into more depth with the methods that they thought they could connect with data for their own research questions.
I was particularly surprised by the ways that students built on their own strengths in devising their projects. One pair of students made a rich database of nineteenth-century publication data using some prior advanced knowledge of Excel, and that was all they really needed to reach some compelling conclusions. One student created a simple virtual world as a way to get familiar with Unity3D, based on a bit of prior programming experience. Another devised a Python script to distant-read a particular theme throughout the corpuses of several nineteenth-century authors. Several students worked intensively with me during labs and office hours to figure out or troubleshoot tasks that had them stumped (e.g., getting data into the right format to work with a D3.js visualization). And much of this work plugged into papers that provided strong disciplinary contexts for the questions they asked of their data. (So by my criterion, I suppose, the student projects were rich in “mature” DH scholarship.) The student projects that came out of the course were astonishingly good, and the consistently high quality of our final meeting’s “project showcase” has hatched plans for a public mini-conference showcase later this spring.
The Knowledges of DH
I’ll close by sharing another unexpected insight from the course, which came from our reading the Liu essay I mentioned above, “Where is the Cultural Criticism in the Digital Humanities?” We read the essay as part of a discussion of the most heated DH “debates,” on the questions of diversity and theory in the digital humanities. Liu’s essay is widely cited in discussions of diversity, in particular, so I’d imagined we’d discuss it in that light.
Instead, we found ourselves talking (and I found myself thinking more afterward) about the turns at the end of the essay, where, in considering the roles of “instrumentality” in scholarship, Liu also seems to be rethinking the kind of knowledge that DH scholarship produces. He writes:
…the appropriate, unique contribution that the digital humanities can make to cultural criticism at the present time is to use the tools, paradigms, and concepts of digital technologies to help rethink the idea of instrumentality. The goal, as I put it earlier, is to think “critically about metadata” (and everything else related to digital technologies) in a way that “scales into thinking critically about the power, finance, and other governance protocols of the world.” Phrased even more expansively, the goal is to rethink instrumentality so that it includes both humanistic and STEM fields in a culturally broad, and not just narrowly purposive, ideal of service.
I think Liu is suggesting that getting our hands dirty with digital tools (both by using computational techniques and by studying computational culture) puts us in a position where our metacommentary could produce fresh insights about the forms and technologies of knowledge in the contemporary moment. I like this because it suggests that the main benefit of humanists using “big data,” for example, is not simply some well-mapped and -ordered fingertip command of all the data of culture. Rather, what we get is a more robust understanding of “big data” as an idea and as a cultural phenomenon, an understanding that comes from trying to square this new form of knowledge with humanistic strategies of thinking.1
For me, this insight happily supersedes the old “hack vs. yack” debate from the early days of DH. On the one hand, “hacking” makes scholars and students more active and insightful consumers of technology, which is one way of saying that it provides the kinds of digital literacy—the ability to create and manipulate content—that I believe ought to be an essential part of a twenty-first-century liberal arts education. Nevertheless, the know-how of “hacking” ought not to be confused with special expertise, since most DH work can be, and is, done with sub-bachelor’s-level computer science knowledge. (I’m pretty sure David Golumbia has been saying this for years.) Exposure to digital humanities gives humanities practitioners literacy, not expertise; our expertise has always been in our strategies for rethinking and reframing difficult but important questions. (Thinking in this way, the value of DH tools likewise comes primarily from the thoughtfulness with which they’re constructed, secondarily from the uses to which they’re put.) To put the point I get from Liu in one more way: the “theory” (or “yack”) DH needs is broader than a particular canon of interdisciplinary thinkers, and broader than calls for diversity, both of which are important and also deserve constant rethinking and renewal. Theory, as a historicist, self-reflexive, and interdisciplinary account of culture, stands to be enlarged and also renewed through our encounters with the forms, media, and techniques of contemporary information culture.
The chance to think more about such opportunities has me excited to teach my next seminar in digital humanities.
1 A longer discussion here might talk about moving beyond a Foucauldian paradigm wherein the panopticon serves as an unfortunately limited model for contemporary forms of knowledge, and one that often serves to reinscribe a “two cultures” model of knowledge. This is where Liu’s call for a newly robust science and technology studies rings truest to me. (And although it suggests that I not say “paradigm,” Paul Grimstad’s essay “Against Research” is quite interesting in this regard.)