04:30 PM to 07:10 PM M
Krug Hall 19
Section Information for Spring 2023
The availability of text data has exploded in recent times and so has the demand for analysis of that data. The goal of this course is to learn the fundamentals of quantitative analysis of text from a social science perspective. The emphasis is on applications and, while there will be some theoretical treatment of the topics at hand, the primary aim is to help students understand the types of questions we can ask with text and how to go about answering them. We will discuss how texts may be modeled as quantitative entities and how they might be compared. We will also cover supervised and unsupervised machine learning methods. Ultimately, our goal is to help everybody conduct their own text as data research projects and this seminar will hopefully provide the foundation on which more technical research can be built.
View 9 Other Sections of this Course in this Semester »
Enrollment limited to students with a class of Advanced to Candidacy, Graduate or Non-Degree.
Enrollment is limited to Graduate level students.