Universität Mannheim / Sowi / Eitm / english / EITM Europe 2018 / Automatic Text Analysis and Machine Learning

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 textual data. 

Nicole Baerg is a Lecturer (Assistant Professor) at the University of Essex. Previously she was a Assistant Professor at the University of Mannheim. Nicole's expertise is in political economy, with a special emphasis on central banking and political textual analysis.

The syllabus for the course can be found here.