Introduction to Text as Data
Computational tools that identify patterns in language and text increasingly help us understand the world. In this course we will explore several of the most common types of text-as-data analyses, such as collocations, keywords in context, topic modeling, and sentiment analysis. Students will work in teams throughout the semester to apply these tools to understand media coverage of a group or topic of their choice. This course is designed to be accessible to students in the social sciences, humanities, and arts as well as being of interest to computer science, math, and science students. 3 hrs. sem. (Methods)/