Computational Analysis

Perspectives on Computational Analysis (MACS 30000), University of Chicago, M.A. Program in Computational Social Science: Autumn 2016, Autumn 2018

Perspectives on Computational Analysis is the first course of the three-course core sequence in the M.A. Program in Computational Social Science at the University of Chicago. I helped develop this course with Dr. Benjamin Soltoff. I was a co-instructor of the course in Autumn 2016 and the sole instructor in Autumn 2018.

This course gives students an introduction to computational social science data and research design approaches. We use as our main text the innovative new book, Bit by Bit: Social Research in the Digital Age by Salganik (2018), that takes the students through examples, strengths, and pitfalls of large digital data in the form of observational data, survey data, experiment data, and collaborative crowd-sourced data. We also spend time discussing the ethics of social scientific data and privacy issues. In each topic of the course, we go through seminal recent literature. Problem sets involve simple relevant computational problems, as well as written responses to questions about particular papers. A goal of this course is to introduce students to important recent literature, data, and approaches in computational social science. All the syllabus, references, and assignments for the course are available in the GitHub repository for the Autumn 2018 section of MACS 30000.