Time and place: 3:00-4:15 PM on Monday and Wednesday, in CCB 52. Office hours are Wednesday 4:15-5:15 PM in CCB 316.
The principle aim for this graduate seminar is to develop a broad understanding of the emerging cross-disciplinary field of Computational Social Science. This includes:
- Quantitative analysis of social phenomena
- Models of network structure
- Methods for text analysis
- Applications to social science fields, such as political science, sociolinguistics, sociology, and economics
Additional learning objectives include:
- Reading and understanding contemporary research papers
- Presenting concise and informative summaries of published research
- Executing computational social science research, through labs and a replication project
Monday readings will be about computational methods. They will largely be drawn from the following textbooks, all of which are available online:
- An Introduction to Statistical Learning by James, Witten, Hastie, and Tibshirani
- An Introduction to Natural Language Processing by Eisenstein
- Bit by Bit: Social Research in the Digital Age by Sagalnik
- Networks, Crowds, and Markets by Easley and Kleinberg
Wednesday readings will usually be research papers, mostly from the social sciences. These readings will be presented by teams of 2-3 students. We will also spend half of (most) wednesdays on in-class labs.