The course will provide an overview of the methods used in the field of computational social science (CSS) and their real-world applications. It will include both theoretical explanations of different methods and hands-on practical exercises through which the participants will be able to apply the discussed techniques in R. The course is aimed at participants with no or little experience with computational methods. Within the course, topics such as web scraping, foundations of computational text analysis, data visualization, and ethical aspects of CSS will be covered. The course will take place in person and will consist of a combination of lectures and practical exercises. By the end of the course, each participant will have practical experience in R in retrieving web data, applying basic text analysis techniques to it, and visualizing the results. The participants will gain this experience through supervised practical exercises as well as through group projects on which they will work semi-independently, with guidance from the lecturers, throughout the course. To make full use of the course participants should have knowledge of the very basic concepts of programming in R (for example write a loop themselves, read in a CSV file and be familiar with data types such as a data.frame), we link to a self-assessment test below (see Course Prerequisites). To gain that basic knowledge, several pointers to online crash courses on those very basics of R are linked below (see Course Preprequisites). Participants are expected to work through some of those materials before the course should they have never worked with R before at all or only had very limited experience with R.

 

For additional details on the course and a day-to-day schedule, please download the full-length syllabus.

By the end of the course participants will:

 

 

Participants should bring their own laptops and pre-install the following software/packages: