Code

COMPGW01 (Also taught as: COMPM040)

Year

4

Prerequisites

Normally offered only to students in computer science related programmes because basic programming skills are required. 

Term

1

Taught By

Shi Zhou (100%)

Aims

This module aims to introduce important breakthroughs in recent research on analysing and modelling large-scale complex networks in the real world. The class gives a particular focus on the Internet, the World Wide Web and social media networks. Topics covered include the measurement and structure of networks, methods for analyzing network data, mathematical models of networks, percolation and epidemics on networks, the Internet topology, structure of the Web structure, Web search, the emergence of social media networks, and Web analytics.

Learning Outcomes

On successful completion of this module the students will be able to:

• Define and calculate basic network metrics.
• Relate network properties to network structure and evolution.
• Explore how to practically analyse large-scale network data.
• Describe structural features of the Internet and the Web.
• Design and conduce simple Web analytics.

Complex networks

• Mathematics of networks          
• Network measures and metrics
• Large-scale structure of networks
• Random graphs and generative network models
• Percolation and network resilience
• Epidemics on networks

The Internet topology

• Router and AS level graphs
• Disassortative mixing and rich-club phenomenon
• Internet topology generators

Structure of the Web

• Web as an directed graph
• Similarity vs popularity
• Hubs and authorities
• Pagerank

Social media networks

Web analytics

• Measuring the success of Blogs
• Quantifying the impact of Twitter
• Analysing performance of Videos

Lectures and lab sessions.

A website or/and moodle webpage will be created for the course and the course materials such as lecture notes, online resources, sample codes, will be shared. By using moodle, students will also be able to discuss relevant ideas and have questions answered by the lecturer.

• Unseen 2.5 hour examination (70%)
• Coursework (15%)
• Independent Project (15%)

To pass the module students must achieve a pass mark of 50% when all elements are combined.

[1]   S. N. Dorogovtsev, Lectures on Complex Networks, Oxford University Press, 2010.

[2]   M. E. J. Newman, Networks: An Introduction, Oxford University Press, 2010.

[3]   D. Easley and J. Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press, 2010. (Free available online)

[4]   A. Kaushik, Web Analystics: The Art of Online Accountability and Science of Customer Centricity, Wiley Publishing, 2010.

Other books for interest:

[5]   M. Mitchell, Complexity: A Guided Tour, Oxford University Press, 2009.

[6]   M. Dodge and R. Kitchin, Atlas of Cyberspace, Pearson Education, 2001.

[7]   S. N. Dorogovtsev and J. F. F. Mendes, Evolution of Networks: From Biological Nets to the Internet and WWW, Oxford University Press, 2003.

[8]   D. J. Watts, Small Worlds: The Dynamics of Networks between Order and Randomness, Princeton University Press, 1999