Introduction to Computational Social Science with R

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 Prerequisites). 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.

Course leader

Dr. Aleksandra Urman, Dr. Max Pellert

Target group

Participants will find the course useful if:
They are social scientists with very little or no experience with computational methods who would like to learn more about the methods and potentially use them in their research

Course aim

By the end of the course participants will:
- Be able to define what constitutes the field of computational social science and know which methodologies are commonly utilized in the field as well as which types of research questions can be handled using these methodologies
- Be familiar with the major ethical aspects of conducting computational social science research
- Have hands-on experience gathering digital trace data from online sources through direct web scraping and APIs using R
- Know about the basic computational text analysis methods and have practical experience utilizing some of them using R
- Be able to visualize their data using various techniques in R
- Be equipped to use provided pointers to advanced materials to further improve their skills

Fee info

EUR 500: Reduced fee for enrolled students, and unemployed persons

Prerequisite for the reduction is a certificate of enrollment / employment status valid at the time of the Fall Seminar.
EUR 750: Participants from universities and non-commercial institutions

Scholarships

none