Humanities Text Mining and Meaning

Description from DukeHub

The digital text has led to new forms of research and is receiving increasing attention from artificial intelligence (AI). The application of machine learning to text, known as text mining, presents unique intellectual challenges that require major contributions from the humanities. This course introduces students to the interdisciplinary domain of text mining through a humanities-based media-theoretic framework. Students will first learn text data prep skills and practices fundamental to meaningful analysis. The semester will later introduce unsupervised machine learning and topic modeling, and culminate in a group project. Not recommended for advanced CS students.

Skills

• ai and machine learningdescription: "artificial intelligence" and 3 more
• data and statisticsAI review: "learn text data prep skills and practices fundamental to meaningful analysis"

AI-resilient: 0 of 5 0/5

• No: Physical, lab or field work
• No: Live work with people
• No: Judgment someone is accountable for
• No: A craft you practice with your hands or body
• No: Small, in-person format

The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works

More in CMAC

• Global Digital Media: Critical and Comparative Approaches to Information Technologies CMAC 210S
• Social Marketing: From Literary Celebrities to Instagram Influencers CMAC 253
• Digital Feminism CMAC 265S
• Wikipedia, AI and the Future CMAC 390S-10
• Cmac:duke-DKU Pres Lab Project CMAC 490-01
• Cultural Analytics CMAC 590S-02

All CMAC courses · All of Undergraduate