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SOCIAL NETWORK ANALYSIS
PROGRAMMES
M.Sc. Social Computing
M.Sc. Applied Informatics
M.Sc. Business Analytics
1. Learning Outcomes
On successful completion of the project, students should be able to:
A. Demonstrate a critical and in-depth understanding of Social Network Analysis (SNA), including well-defined concepts, models, algorithms, and applications.
B. Analyse and compare the strengths and weaknesses of different social network models and algorithms.
C. Apply the key elements of SNA to develop solutions for real-world problems.
D. Design and implement social network computer programs for practical applications.
E. Implement and optimize algorithms for social network analysis.
The assessment is designed according to the learning outcomes stated above.
2. Essential Resit Project Requirement – Proposing a Topic
Propose the project topic and dataset as early as possible (within the first two days of the resit period). The topic and dataset selection are on a “first-come, first-served” basis. You are not allowed to choose the same topic and dataset as your final project and that of other students, i.e. their original submissions and for this resit. Email your project topic and dataset to [email protected] for review and approval before starting any work.