Political Science 797TA - ST- Text as Data

With the recent explosion in the availability of digitized text, social scientists increasingly are turning to computational tools for the analysis of text as data. In this three-credit course, students will first learn how to convert text to formats suitable for analysis. From there, the course will introduce and proceed through tutorials on a variety of natural language processing approaches to the treatment of text-as-data. This will include relatively simple dictionary approaches for measurement, supervised learning approaches for document classification, vector representations, contextualized embeddings, and more.

This course is open to Political Science Graduate students only. Familiarity with R (and likely Python) is valuable but not necessary.