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SDSC3016 - Social Network Analysis

Offering Academic Unit
Department of Data Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
Course Offering Term*:
Semester A 2024/25
Semester B 2025/26 (Tentative)

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

This course provides students with an extensive exposure to the elements of social network analysis, with an emphasis on applications for online social media. Topics include graph theory, complex network perspectives, social science perspectives, ego-networks, tie formation, link prediction, information cascading, bipartite/multipartite networks, dynamic networks, signed networks, and community detection.


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

Continuous Assessment: 50%
Examination: 50%
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

SDSC3016.pdf

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