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, political scientists increasingly recognize automated text analysis as viable approach to analyzing social and political behavior. This course – in which we use R – introduces students to a variety of its methods and tools, ranging from dictionary methods and other supervised and unsupervised methods to learn about, for example, content, ideology and sentiment in text. The course – which combines lectures and practical 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.