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DSC2005 - Introduction to Computational Social Science

Offering Academic Unit
Department of Data Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
DSC1001* and DSC2001

 *Pre-requisite DSC1001 will be exempted for students who are enrolled in Minor in Data Science
Equivalent Course(s)
SDSC2005
Course Offering Term*:
Semester B 2026/27

* The offering term is subject to change without prior notice
 
Course Aims

Data science centers 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, behavioral analytics, text mining, and social research ethics.


Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 50%
Examination: 50%
Examination Duration: 2 hours
Min. Continuous Assessment Passing Requirement: 30%
Min. Examination Passing Requirement: 30%
 

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

DSC2005.pdf