This course will guide students through advanced applications of computational methods for social science research. Students will be encouraged to consider social problems from across sectors, like health science, education, environmental policy and business. Particular attention will be given to the collection and use of data to study social networks, online communities, electronic commerce and digital marketing. Students will consider the many research designs used in contemporary social research and will learn to think critically about claims of causality, mechanisms, and generalization in big data studies. Graduate requirements include additional readings and a more in-depth final paper than is required at the undergraduate level.
Data Types: Numerical, Categorical, Networks, Text
Methods: Network analysis, Descriptive statistics, Frequentist inference, Machine learning, Data management, Visualization
Substantive Areas: Discrimination/Inequality, Ethics/Privacy, Science/Reproducibility, Web/Social Media
Programming Languages: Python, Unix