For the last few years one of the classes that I have given is the Introduction to Computational Social Science (CSS). This is often the first class many students take within our program and as such its objectives are:
- To understand the motivation for the use of computational models in social science theory and research, including some historical aspects (Why conduct computational research in the social sciences?).
- To learn about the variety of CSS research programs across the social science disciplines, through a survey of social simulation models (What has CSS accomplished thus far?).
- To understand the distinct contribution that CSS can make by providing specific insights about society, social phenomena at multiple scales, and the nature of social complexity (What is the relation between computational social science.
- To provide foundations for more advanced work in subsequent courses or projects for those students who already have or will develop a long-term interest in computational social science.
The course surveys computational approaches such as system dynamics, social network analysis, machine learning, cellular automata, discrete event simulation, agent-based modeling, and microsimulation to study social phenomena with emphasis on complexity theory.
On thing that all the students need to do during the semester is create a computational model investigating a social science research question. This exercise is often their first model that many students ever create. Below you can see some of this years models. Most of the models where created in NetLogo.