This course provides students with an extensive exposure to the fundamental principles and essential techniques of computational social science methods, ranging from automatic collection of digital and online data to machine learning with or without human supervision. The methods are intended to complement and enhance the traditional social science methods of data collection and analysis, such as survey, experiment, content analysis, and statistical analysis. Topics include opportunities and challenges for computational social science research in the digital age, descriptive/predictive vs. explanatory research, found data versus made data, research design, causal inference, sampling of social media, online experiment, behavioural analytics, text mining, and online research ethics. The course is useful for students who are interested in using computational methods for social, cultural, business, legal, and other areas of research.

Continuous Assessment: 100%