I have taught Computational Social Science at the National University of Kyiv-Mohyla Academy (est. in 1615) since 2022.
Course description
Computational social science refers to the academic sub-disciplines concerned with computational approaches to the social sciences. It investigates social and behavioural dynamics through social simulation, (social) network analysis, and social media analysis.
In this course, I teach what CSS is, how to get needed data, and how crowdsourcing works. During the course, students learn how to model disease dynamics (COVID spreading, for example) and (social) network processes, some basics of statistics in social science, and how to build human-oriented experiments.
The course requires a lot of involvement from the student’s side.
In the final project, students analyze human behaviour where the central subject of the research is student themself.
Course format
This course contains 7 lectures, 5 homeworks, and the final project, which is a summarization of the last 3 homeworks.
Main course goal and objectives
To learn how to approach different human-related computational problems, how to organize data science around society and networks, and how to collect different data.
Course plan
- What is Computational Social Science?
- Data: collection, banks and tools
- Data Visualization & Presentation
- Crowdsourcing. Amazon Mechanical Turk part 1
- Amazon Mechanical Turk part 2
- Network Science
- Statistics for the Behavioral Sciences
Feedback
TBD
