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Dear Future Graduate Students,

It’s that time of year to start thinking about grad school. Recruiting is not easy for me. My general sentiment around graduate training is, let them decide. Advertising or persuasion is for places like Trump University not scholarship. But I think we are at a bit of a crossroads in our field and I am concerned that too many people aren’t making good choices, potentially because of what they’re hearing from their faculty. After all, the ratio of people doing computational humanities to those who are not is tiny. The messaging is bound to be skewed. It seems important therefore to go out on a limb (yes it feels like a limb) and try to articulate why you should orient your work towards a more data-driven approach. So here goes.

Why does your dissertation need data? Because it opens up so many more questions. When your only method is to read as much as possible, first, you’ll always come up short. You can never read enough and you’ll always know it. This is one of the reasons we like to parade our erudition. It’s to cover over our knowledge of what we know we don’t know. Second, you have no principled way of making judgments about all that you have read as a whole. You have no way to contextualize those insights, to put it in conversation with the things you haven’t read. To put it another way, you have no way to generalize about what you are finding. If you want to talk about the politics of modernism or the spectrality of televisual personalities, watching or reading alone isn’t going to get you there in a convincing way. Data isn’t the be all to end all. But it does solve problems. It answers questions that you will not otherwise be able to pose.

There’s another reason too, one that I think is almost more important because it isn’t about a particular subject area. Rather, it’s about your position in the field more generally. Every day thousands of dissertations are uploaded to ProQuest. And every day we know a little bit less about our respective fields. The more research there is, the harder it is to have a sense of the field as a whole — and where your place is within it.

I remember, very distinctly, a moment I had one day wandering through the stacks as a graduate student at Columbia University, the home of Melvil Dewey. I remember thinking to myself, holy s%*t, look at all these books. What is the point of me writing one more? The aggregate value of one more book decreases every day. But the ability to use data to understand that whole to which you yourself are a contributor: that is invaluable. And you can’t get there by reading alone. Only data can do this, for better and for worse.

I know people will tell you it’s a bad idea. Or that it’s a fad. It’s not. It’s an essential part of the research process. You should be thinking about programs that will help you integrate it into your research, be able to guide you towards using it effectively and thoughtfully, and above all champion methodological plurality rather than dogma. If you’re hearing something else then you aren’t being given very good advice.