GESIS Training Courses

Scientific Coordination

Marlene Mauk
Tel: +49 221 47694-579

Administrative Coordination

Noemi Hartung
Tel: +49 621 1246-211

Introduction to Computational Social Science with R

Online via Zoom
General Topics:
Course Level:
Software used:
Students: 550 €
Academics: 825 €
Commercial: 1650 €
Additional links
Lecturer(s): Johannes Gruber

About the lecturer - Johannes Gruber

Course description

The Digital Revolution has produced unprecedented amounts of data that are relevant for researchers in the social sciences, from online surveys to social media user data, travel and access data, and digital or digitized text data. How can these masses of raw data be turned into understanding, insight, and knowledge? The goal of this course is to introduce you to Computational Social Science with R, a powerful programming language that offers a wide variety of tools, used by journalists, data scientists and researchers alike. Unlike many introductions to programming, e.g., in computer science, the focus of this course is on how to explore, obtain, wrangle, visualize, model, and communicate data to address challenges in social science. The course emphasizes the theoretical and ethical aspects of CSS while covering topics such as web scraping (obtaining data from the internet), data cleaning (getting raw data into a table or otherwise easy-to-analyze format) and visualization (i.e. drawing bar, line, scatter plots and more from data), automated/computational text analysis (i.e. using the computer to find patters in text or sort documents into categories), machine learning (i.e. training algorithms on annotated data and generalizing patterns to unseen data), network analysis (i.e. examining relationships among entities, such as persons, organizations, or documents) and agent based modeling (i.e. simulating interactions between such entities). The course will be held as a blended learning workshop with video lectures focused on theoretical background and demonstrations accompanied by live online sessions where students can ask questions and work through projects together.
Organizational Structure of the Course
The course will take place in a blended learning format. That means that you will need to (1.) read the literature listed under each session (if any); (2.) watch the video lecture; (3.) finish the exercises before each live group session. This means that participants will be on roughly the same level of knowledge during the live sessions and we will be able to focus on open discussion, the answering of questions and small group exercises.

Target group

You will find the course useful if:
  • you have taken, e.g., a statistics course, know a little bit of R, and now want to explore computational methods, data science or one of the approaches listed above.

Learning objectives

By the end of the course, you will:
  • be able to define what constitutes the field of computational social science;
  • have a high-level overview of the approaches utilized in computational social science, including advantages and shortcomings;
  • have a basic knowledge and hands-on experience of how to apply the approaches and what tools are considered state-of-the-art;
  • be equipped to deepen their knowledge on the theory and practice of computational social science.


  • Working knowledge of R is required. You should take the self-assessment test I prepared here: If you do not know enough R to comfortably solve all or at least most of the exercises there is a list of recommended crash courses at the end of the self-assessment site. If you need more help, you should take the "Introduction to R" course that takes place online from 27-29 August.
Software and Hardware Requirements
We will work with R and RStudio in the course. But you can of course use an IDE different from RStudio if you prefer. I will provide a script that installs and/or updates all R packages we need during the course. You will need a version of R newer than 4.1.0. I also recommend you use an updated version of the Zoom client for the live sessions (a good camera and mic would also be preferable).