INFO 3350

Text Mining History and Literature

Course Description

Course information provided by the 2025-2026 Catalog.

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.

Enrollment Information REF-F25 Primarily for: students with programming and data science experience, or permission of instructor required.

Distribution Requirements (OPHLS-AG), (SDS-AS)

Last 3 terms offered 2024FA, 2023FA, 2022SP

Learning Outcomes REF-FA25

• Describe and evaluate major existing results in quantitative humanities research.
• Recognize, explain, evaluate, and implement standard techniques for the use of text as data.
• Create reliable, compelling, data-driven humanities research reports that apply suitable text-mining methods to existing humanities questions.
• Identify and analyze historical, ethical, and epistemic limitations of existing and potential textual corpora.
• For graduate students: Evaluate and adapt text-mining methods to current research problems relevant to the student's work.
• For graduate students: Analyze, evaluate, and present current research findings in computational text analysis.

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