The Use of Social Science Computer Programs

Course Overview

As more advanced and specialized quantitative methods have become increasingly common in the social sciences, graduate students must develop a wide range of computational skills to keep up with emerging literature. Though R remains the dominant programming language in the social sciences, its limitations have prompted a new generation of scholars to learn Python alongside R. Therefore this course covers both advanced methods in R and the basics of Python, emphasizing areas of overlap between the two languages where they exist. We will also cover several “computationally intensive” methods that have received widespread attention in the literature - networks, text as data, machine learning, and LLMs - culminating in a final project in which you can explore these methods on your dataset of choice. The goal of this course is (1) exposure to modern computational social science methods and (2) literacy to teach yourself additional methods and skills in the future as needed for your research.