CONN 302 | Literary Text Mining

Literary text-mining is a decades-old field that uses quantitative methods to answer enduring literary questions about texts' meaning, significance, politics, context, and more. Text-mining methods offer researchers the chance to answer new questions at larger scales. This course introduces students to a variety of computational methods, from foundational counting methods to machine-learning. Students will investigate several literary datasets using Jupyter notebooks or Pycharm and the Python programming language. No prior experience in literary theory or Python is required; different paths through the course are available for students with significant coding experience.