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Data Across the Curriculum: Qualitative Literary Analysis in the Humanities

This semester, students in Professors James Lee and Erik Simpson’s special topic seminar, “Milton, Blake, and Frankenstein,” will use NVivo, a software for qualitative literary analysis, to create word trees visualizing the use of the word “sublime” in Milton’s work. This is an outgrowth of teaching that Lee began in 2013 when, as DASIL’s first Faculty Fellow, he designed a seminar on Shakespeare and Renaissance literature that used NVivo to investigate first the corpus of Shakespeare’s work and then over 20,000 documents from the Early English Books Online (You can see previous DASIL blog posts written by Prof. Lee about this research here and here).

Lee’s classes use NVivo to visualize data and generate descriptive statistics about datasets that can be exported to other programs, such as Tableau (another software for data visualization). These programs are particularly useful to students because they provide a user interface, allowing students to manipulate data easily, without having to learn a new programming language.

Lee’s personal research incorporates some of the same methodologies that he teaches to his students in class. His current project, the Global Renaissance Project, is partially funded by a “Digital Bridges for Humanistic Inquiry” grant from the Mellon Foundation. It uses network analysis and topic modeling to examine discourses surrounding race in Renaissance texts. The figure below is a still of the prototype for the topic modeling aspect of the project, which identifies clusters of words with a disproportionately high probability of occurring together in text.

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So far, the project has revealed that Renaissance representations of race were centered on cultural, geographic, and commercial factors; race as a biological or physical concept emerged as a justification for English imperialism after the Renaissance. Lee currently collaborates with professors at the University of Iowa on a “linked reading” project that combines two databases to discover how networks of printers and publishing houses contributed to the Renaissance discourse on race.

For Lee, the biggest challenge presented by the integration of digital analysis into classes is changing his students’ mindsets. He observes that humanities students are often used to classes in which students and professors develop ideas through discussion. In contrast to discussion-based classes, working with the digital humanities can mean that students exert effort in a particular line of inquiry that doesn’t yield any concrete results.

The iterative process of data analysis can be frustrating, especially since students often don’t anticipate undertaking it in their humanities courses. Professor Lee hopes continuing to integrate digital humanities into classes like the seminar he is co-teaching this semester, will help to convert students’ frustration into a “tinkering mentality” so that students come prepared to continually adjust their hypotheses based on their analysis and visualization of the data.

To explore the Global Renaissance Project prototype, click here.

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