Automatic Text Analysis and Machine Learning
Nicole Baerg (University of Essex)
July 2 - July 4
The course, "Automatic Text Analysis and Machine Learning," will cover working
with political textual data and supervised learning methods such as dictionary
methods, clustering approaches, and machine learning techniques for labeled
data (Naive Bayes, SVM, Trees, Random Forests, etc). The course will also cover
how to annotate your own data for use in ML approaches. The class will also
cover ideological scaling techniques and introduce some new tools for scaling
Baerg is a Lecturer (Assistant Professor) at the University of
Essex. Previously she was a Assistant Professor at the University of
Nicole's expertise is in political economy, with a special emphasis on
banking and political textual analysis.
The syllabus for the course can be found here.