This syllabus is indebted to just about everyone who has posted a syllabus for a DH course, and especially to Paul Fyfe, from whose draft syllabus I borrowed several readings.
The syllabus itself is here as a .pdf file.
As you’ll see if you download it, this is not a general digital humanities course. At Urbana-Champaign, John Unsworth has been teaching an introduction to digital humanities in the Graduate School of Library and Information Science, and there’s no way I could hope to replicate his breadth of knowledge. Instead I’ve focused on literary and historical applications of text mining, because that’s an area where I feel I can teach skills that a wide range of humanities graduate students will find immediately useful.
I realize the choice of focus may seem odd, since text mining is a relatively controversial subfield of DH, and a technically challenging one. There’s no way to duck the technical challenge: I am going to try to teach enough coding (using R) to empower students to define their own questions and visualize their own results. But I don’t think controversies about quantification need to be a problem, since I approach text mining largely as a discovery strategy. I hope it will turn up insights and clues that students find useful, without necessarily compelling them to add a lot of numbers or graphs to their arguments.
The “tools” and “theory” in the title of the course are not meant to be pitted against each other. The title instead flags a working assumption that practice and theory are fused: our interpretive theories are already shaped by the social/technical infrastructure we use to find and read texts, so reflectively reshaping that infrastructure is a way of “doing theory.”