Instructor: Shashi Prabh
Email: shashi.prabh@snu
Office: D036E
Office hour: Wednesdays 10 - 12 PM, or by appointment
Lectures: 4:00 - 4:55 AM Mon, Wed and Fri (B012)
Seemingly disparate networks, such as the world wide web, telecommunication networks, social networks, neural networks and protein-protein interaction networks, share common properties. This course will introduce some of the common properties shared by a variety of networks models, and will introduce methods to analyze and predict the behavior of large-scale networks.
None. Knowledge of probability at high school level will be helpful.
Basics of graph and probability theory
Technological, social, economic and biological networks
Network metrics
Structure of large-scale networks
Small-world model
Random networks
Power-law networks, models of network formation and growth
The course will primarily use materials available on-line in the public domain. The following books can be used for supplementary reading.
D. Easley and J. Kleinberg. Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge University Press, 2010.
M. E. J. Newman. Networks – An Introduction. Oxford University Press, 2010
Quizzes: 50%
Project: 50%
Due date: Blackboard upload: Nov 29 Midnight, Hard copy: Nov 30 before the test.