Undergraduate Program Status
Automated text analysis has become very popular across the social sciences over the last few years. With the massive availability of text data on the web, social and political scientists increasingly recognize automated text analysis (or “text as data”) as a useful approach to analyzing social and political behavior. This course – in which we use R – introduces students to a variety of its methods and tools to learn about, among other things, content, ideology and sentiment in text. The course – which combines lectures and coding sessions – will be hands-on, with an emphasis on dealing with practical issues in each step of the research process (ranging from collecting and pre-processing text data to validating and visualizing output of the analysis). Students who have finished this course are well-positioned to apply automated text analysis methods in their own work, and will be able to critically evaluate existing work.
This course introduces students to various approaches of automated text analysis in social science research, emphasizing hands on analysis of real (political) texts. Students will learn how to extract useful quantities of interest from text, evaluate the outcomes and write up the results of an analysis that uses automated text analysis. Furthermore, students will be able to critically evaluate (social science) research that uses automated text analysis methods.