COMPGW01 - Complex Networks and Web

This database contains 2017-18 versions of the syllabuses. For current versions please see here.

CodeCOMPGW01 (Also taught as COMPM042)
PrerequisitesNormally offered only to students in computer science related programmes because programming skills are required for the coursework project.
Taught ByShi Zhou (100%)
AimsThis module introduces the fundamental concepts, principles and methods in the interdisciplinary academic field of network science, with a particular focus on the Internet, the World Wide Web and online social media networks. Topics covered include graphic structures of networks, mathematical models of networks, the Internet topology, structure of the Web, community structures, epidemic spreading, PageRank, temporal networks and spatial networks.
Learning Outcomes

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

  • Define and calculate basic network graphic metrics.
  • Describe structural features of the Internet and the Web.
  • Relate graphic properties to network functions and evolution.
  • Explore new angles to understand network collective behaviours.
  • Design and conduct analysis on large network datasets.



Network structures
The Web structure
Network properties
Random graphs
Small-world networks
Scale-free networks
Network generative models
Rich-club coefficient
Network mixing patterns
Network structural constraints
Network centrality
Internet topology and models
Network visualisation
Weak ties in networks
Network community structure
Network cascades
Epidemic spreading
Network controllability
Document networks
Temporal networks
Spatial networks
Signed networks
Twitter botnets
Web analytics

Method of Delivery

A Moodle webpage is created for the course. All course materials, such as lecture notes and online resources will be shared. By using the Moodle, students will also be able to discuss ideas and questions with the lecturer and other students.


The module has the following assessment components:

  • Unseen written examination (2.5 hour, 70%)
  • Course project (30%)
    • The Course Project consists of an individual project on network data analysis. Programming is usually required and a project report (3000 words), including literature survey, which is due by the end of the Winter Holidays.

To pass this module, students must:

  • Obtain an overall pass mark of 50% for all components combined.


Reading list available via the UCL Library catalogue.