Introduction to Quantitative Text Analysis

About

This course is offered as part of the Radboud Summer School in Social Research Methods, in collaboration with MethodsNET (a global network that offers excellent training in social research methods).

You learn how to prepare, scale, and classify text data in R. You will use both supervised and unsupervised methods and apply the various techniques on a wide range of text corpora.

Course leader

Lisa Lechner Assistant Professor of Methods and Methodology Department of Political Science University of Innsbruck

Target group

-Master
-PhD
-Post-doc
-Professional

This PhD level course is open to all researchers aiming at bringing their research to the next level. It is designed for those who have research projects on their desk or in their mind involving text data. Students with R-experience will enjoy the course even more as they spend less time learning R and more time analysing exciting text corpora.

Course aim

After this course you are able to:

-Set up efficient workflows for quantitative text analysis (QTA).
-Clean and prepare texts to conduct QTA.
-Classify texts using supervised and unsupervised techniques.
-Scale texts using supervised and unsupervised techniques.

Fee info