The Minor in Computational Social Science enables College students in the social sciences to build fundamental computational skills with the purpose of enriching existing approaches to social scientific inquiry. Additionally, for College students outside of the social sciences (e.g., in the physical and biological sciences), it provides an opportunity to consolidate their computational, mathematical, and statistical skills, as well as apply these skills to questions about social and cultural life.
Over the course of the program, students will learn how computational approaches complement and expand upon traditional research designs in the social sciences, as well as gain the hands-on computer programming and data analysis skills necessary to implement these computationally-enhanced research designs. For instance, students will learn how “big data” and AI technologies enhance traditional observational studies, explore simulation-based research designs, as well as investigate how to run large, computationally-enhanced surveys and digital experiments. They will additionally have the opportunity to explore advanced approaches for applying their computational and analytical skills to social science problems in elective courses in Computational Social Science. For example, students may complete Machine Learning and High-Performance Computing coursework, with an emphasis on applicability to social scientific research.