Introduction to Computational Social Science with R

GESIS Fall Seminar 2025

Authors
Affiliations

Johannes B. Gruber

GESIS

John McLevey

University of Waterloo

Welcome to the Course

This is the course material for the GESIS Fall Seminar in Computational Social Science 2024 course Introduction to Computational Social Science with R, 01.09 - 05.09.2025.

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.

Course Schedule

Day Session Materials
Day 1 Introduction to Computational Social Science Slides
Day 2 Obtaining Data Slides
Day 4 Computational Network Analysis Slides
Day 3 Computational Text Analysis Slides
Day 5 Social Simulation & Agent-based Models Slides

Quick Start

Required Software

Before starting the course, please install:

Download Course Materials

Clone this repository using RStudio:

  1. Create a new project (top left corner)
  2. Select “Version Control” → “Git”
  3. Use URL: https://github.com/JBGruber/computational-social-science-r.git

Install Required Packages

After cloning, install all required R packages:

if (!requireNamespace("rlang", quietly = TRUE)) install.packages("rlang", dependencies = TRUE)
rlang::check_installed("attachment")
rlang::check_installed("remotes")
rlang::check_installed(attachment::att_from_qmds(path = ".", recursive = TRUE))