Special Topics: Social Data Science

Course Number: 
Semester and Units: 
Intermittent: 12 units
Course Description: 

This course focuses on how to elucidate the true nature of social phenomena using computational techniques and digital data. The goal of the course is that students will be able to explore innovative ways to combine computational and social sciences with understanding the different points of view between them. This course also helps students to have a firm theoretical grounding in the research, analysis, and system building of social computing. Topics covered include agent-based simulations, large-scale data analysis, text as data (natural language processing), digital experiments, mass collaboration, and ethics. The course consists of lectures and exercises to enable students to conduct research in social data science / computational social science on their own.