INFO 3350 - Text Mining History and Literature

(MQR-AS, SDS-AS)

Fall. 3 credits. Student option grading.

Prerequisite: INFO 2950 Intended for: students with programming and data science experience, or permission of instructor required. Co-meets with INFO 6350.

M. Wilkens.

The class will introduce methods for computer-assisted analysis of historical and literary text collections. It will cover corpus curation, representing text as data, building statistical models from text, and interpreting quantitative results. The class will also reflect on how computational methods fit with existing practices in the humanities, and how we can use models as complements to our own interpretations. Following the course, students will be able to assist faculty in quantitative and computational humanities scholarship.