Davide Vega D'Aurelio

1DL007 - Introduction to Computational Social Science

This is a new interdisciplinary course, initially developed in collaboration with Matteo Magnani (IT Department, InfoLab), Miia Bark (Department of Sociology) and Alexandra Segerberg (Department of Government) and taught for the first time in Spring 2022.

Currently the course is coordinated by Victoria Yantseva (IT Department, InfoLab).

The course introduces computational approaches to model human behavior and social phenomena. Core concepts in computational social science are covered, such as observational studies (what types of data exist, possible biases and how to use data for modeling), basic concepts and techniques for running experiments (asking vs. observing, natural experiments, simulations, validity and generalization) and discuss key issues such as ethical considerations.

The course has both a theoretical and a practical perspective, where students learn basic principles and also how to apply them in practice in three main areas:

  1. social network analysis
  2. text analysis
  3. agent-based modeling and simulation.