SDSC2005 - Introduction to Computational Social Science | ||||||||||
| ||||||||||
| * The offering term is subject to change without prior notice | ||||||||||
Course Aims | ||||||||||
Data science centres around data, originated by human or non-human. This course provides students with an extensive exposure to the elements of computational social science that concerns exclusively with human-generated data. Topics include opportunities and challenges for social science research in the digital age, descriptive/predictive vs. explanatory research, found data versus made data, research design, causal inference, sampling of social units, online experiment, behavioural analytics, text mining, and social research ethics. | ||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||
Continuous Assessment: 60% | ||||||||||
Examination: 40% | ||||||||||
Examination Duration: 2 hours | ||||||||||
Note: To pass the course, apart from obtaining a minimum of 40% in the overall mark, a student must also obtain a minimum mark of 30% in both continuous assessment and examination components. | ||||||||||
Detailed Course Information | ||||||||||
| SDSC2005.pdf | ||||||||||
