Exploring the Digital Humanities

Tara Iyer

Stanford University


Mark Algee-Hewitt, a professor of English and Co-Director of the Stanford Literary Lab, focuses on the eighteenth and early nineteenth centuries in England and Germany, seeking to combine literary criticism with digital and quantitative analyses of literary texts. At the Literary Lab, Dr. Algee-Hewitt leads projects on suspense literature, the relationship between titles and texts in the long eighteenth century, and gender performance in the dialogue of novels written during the Romantic period.


TI: The Digital Humanities is a pretty up-and-coming field. Can you tell me a little bit more about it and what projects you’re pursuing right now?


MAH:  It’s a wide ranging term that encompasses many kinds of research, from the use of mapping technology to understand various historical formations, to looking critically with a humanities lens at the way in which technology is shaping our lives. My own particular side of things tends to be less looking at digitality through a humanities lens and more the reverse: looking at humanities-based questions, primarily literary or textual questions, using methodologies that are digital in origin. So, things that would be more native to computer science or statistics or computational linguistics, doing those kinds of activities to answer questions of literary, critical, or historical significance. So, for example, in the literary lab, we have many projects, such as the Suspense Project, in which we are using computational models and social psychology methodology in order to understand why certain texts create the effect of suspense in certain people. We have a project on what’s called Canon Archive that looks at why certain texts become or are considered to be canonical while others are left in the archive and don’t get read anymore—if there’s any kind of morphological or formal differences between those two over time.


TI: Wow, that’s really fascinating.  How do you go about designing a project and then answering these interdisciplinary questions?


MAH: It’s really important that we think of the methodologies that we use as applied science, which is to say that we frequently try and innovate methodologically as part of the process of research. But the goal of the research lies in the field that we’re examining. So first we have the question that is usually a literary question: “Why does the canon exist? Why do some people feel suspense even when they know what’s going to happen in a work? Why do certain texts become viral and really, really popular, despite not having a marketing push behind them?” So we start, usually, by framing the question in terms of something that would be much more familiar to humanities, but still has a way to operationalize the question, such that it can be answered through quantitative means.


Image from Wikimedia Commons

TI: Along that line, how do you think the Digital Humanities is bridging the “techie-fuzzy divide”, as it were?


MAH: (laughing) Or is it bridging the techie-fuzzy divide?


TI: Or is it? Yeah, I think it’s a particularly relevant question at Stanford, because a lot of people think of Stanford as a very “techie” university, where you come and get pulled into this CS vortex, and you work in Silicon Valley. So I’m curious to know how you think the Digital Humanities is changing that.



MAH: I mean I think it is changing it to a certain degree. One of the nice things about working in this field is that, for example, when I teach undergraduate classes and graduate classes on Digital Humanities  methods, I frequently have a fairly even split between humanities students and computer science, statistics, other kinds of applied science students. And that is a forum in which to witness this kind of interaction in a way that you don’t get to otherwise. I mean I’ve collaborated with some computational linguists, I’ve collaborated with some computer scientists on network theory things, and so I kind of know it from the inside, but watching these two groups of students try and talk to each other is a really interesting experience that literalizes that kind of bridge that you’re talking about. And part of it is the realization in the part of both groups that each one has something valuable to offer. In a class like that, the computer science students will come to the table with a really well-established set of methodologies: they’ll understand how computers can help us break down texts, how they can count things, ways in which they can model various kinds of outcomes. But the humanities students bring to the table a great degree of skill in thinking critically about problems and interpreting results, particularly when both the data going in and the data coming out is really messy and/or noisy. The Digital Humanities is one of those relatively rare places where that set of skills is being brought together by both students and, I think, scholars working the area, to understand how we can leverage this kind of computational technology towards problems that don’t easily lend themselves to computation, and the ways in which humanities methodologies can help us make sense of these much more complex, or higher order, problems than typically are solved by computational methods.


TI: So interdisciplinary studies and projects seem to open up new potential for us to look at both the humanities and computer science and technology in new ways. But some people feel that by focusing so much on the intersection of the humanities and the sciences, you lose a lot of important depth that you would get if you studied only English, or you studied only computer science. What is your answer to that question, how do you think people can learn to become really deep and critical thinkers in both areas, but at the same time leverage the potential of that intersection?


MAH:  (laughing) Do you want the long answer, or the short answer?


TI: Whichever one you want to give.


MAH: I teach actually a class that’s now become a core class for STS Science, Technology, and Society, called Data and Knowledge in the Humanities, and one of the things we look at is the emergence of what’s called disciplinary knowledge in the Enlightenment. And that’s the transformation of knowledge production when things like disciplines emerge, when it became less about a kind of broad knowledge over a number of subjects, and to where expertise became associated with a very narrow and very deep set of knowings. And so that notion that in order to be an expert in the field you need very specific, very narrow and discontinuous knowledge, is actually radically historically contingent, it’s only been around for a couple hundred years. Now, our university system is founded on exactly that model of disciplinary knowledge, and that is what we have to work with. But it helps for me to keep in mind that this isn’t necessarily the way it always was, nor is it the way it necessarily has to be. And I think good interdisciplinary work—and it’s hard, because a lot of interdisciplinary work, even in my own field, is not great—but good interdisciplinary work requires a sensitivity and attention to both disciplines, and particularly the points at which they interact. So we can imagine the emergence of a kind of hybrid field rather than these two fields being brought together with still a kind of gap or lacuna between them, but a hybrid field in which people can be deeply knowledgeable about the applied parts of computer science that make sense for humanities, and the ways in which humanities questions can be operationalized through an understanding of computer science.


TI: I think it’s something that has only recently been thought of as an important area of study.


MAH: Absolutely, I mean I’ve been doing this long enough. So I started around 2005-2006 when I was midway through my Ph.D., and even then—I mean, if you listen to historians in the field of digital humanities, people have been doing this for a lot longer than that, I  mean there were studies in the 1960s, the 1970s, humanities computing was a thing in the ‘90s—but even when I started in 2006, this was not a highly populated field, there weren’t a lot of people doing it, and departments on both sides of the divide—both computer science and literary studies, for example—were resistant in many ways. And it’s amazing how, in a few short years since then, things have really changed.


TI: Along with this, where do you think Digital Humanities research is heading into the future—you’ve talked a lot about the different implications, whether it be broadening your research focus, finding new patterns in Supreme Court case studies. In your mind, what is the trajectory of the field right now?



MAH: This is a really hard question. Digital Humanities is getting close to a crossroads, I think, it’s methods are becoming more and more embedded within the humanities departments of which it originally was a member, so that more and more departments are investing more and more of their energy in various formulations of the digital humanities – I mean the fact that I’m an assistant professor of the Digital Humanities at Stanford speaks to the fact that the English department has realized that this is a field that needs representation. On the other hand, things are getting more and more collaborative across different departments, and a lot of scholars have made the argument that Digital Humanities is a field in and of itself that might at some point in the future sever itself from the various constituent departments and reorganize itself around a specialized set of knowledges and practices in and of itself. So, I mean, intellectually, I think, Digital Humanities is going to stay on the path that it’s on: our methods get ever more sensitive, new people are coming into the field bringing really interesting ideas of new ways to think about texts quantitatively or computationally, especially in all these other fields – geohumanities, spatial humanities, design and humanities. But what that will look like in the future, whether we sort of form something new or whether we keep working within our own individual departments, disciplines, clusters–that’s a big question.


TI: I’m excited to see where this field goes. So, it looks like we’re almost out of time – do you have any closing comments?


MAH: You’re absolutely right, it’s an interesting field because of the way in which it combines these different sets of knowledge, and because it’s something that hasn’t been really done before in this way. So doing this work, doing computational studies of text, for example, is really exciting because whatever we do, we tend to discover something that we didn’t know before. And you can tell, I think, whether or not a field is really fruitful by how easy it is, or how readily new kinds of discoveries keep emerging. And this field is rife with that, and we’re pretty lucky here at Stanford, because this has historically been one of the institutions—because of its strong computational program, but at the same time we have a strong humanities program—because of that combination, this has been one of the places where this has emerged. Historically, it’s one of the ones that’s done it the longest, and I think done it the best. So I think it’s a really exciting field to be in, and I think it’s a really exciting place to be in that field.