Computational Social Science
Mastery courses are special types of courses that require students to demonstrate synthesis of the major theories, methods, and approaches to inquiry and/or schools of practice necessary for entry into a particular career in the information professions.
Computational Social Science Mastery Course Description
This course will require students to demonstrate their mastery of applying and developing computational methods, algorithms, and models in order to answer social science questions from an empirical and computational perspective. Students will demonstrate their ability to collect and manage large data sets on human behavior (e.g. social media) and to apply network science, data mining, information retrieval, natural language processing, and machine learning techniques to investigate social science questions about people’s interactions and information. Students will work on semester-long projects that deal with industry-scale data sets and solve real-world problems. Projects will most commonly use social networks but can also involve analysis of other non-social network data (e.g. text) to enable deeper and complementary analysis than that could not be attained by studying social network data alone. Example projects can aim to enrich our understanding of how people and organizations make decisions or to address larger societal issues such as inequality, education, and ideological segregation. Aligned with best industry practices, students will be expected to work in a fast-paced, collaborative environment and to demonstrate independence and leadership.
Selective Required Courses:
and one of: