MA320      Half Unit
Mathematics of Networks

This information is for the 2018/19 session.

Teacher responsible

Dr Andrew Lewis-Pye


This course is available on the BSc in Mathematics and Economics and BSc in Mathematics with Economics. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.


Students must have completed Mathematical Methods (MA100) and Introduction to Abstract Mathematics (MA103).

Course content

Globalisation and the growth of the internet have meant not only an increasing need to understand the way in which social and communication networks form and operate, but also an unprecedented amount of data available to aid in this analysis. The last decade has seen a coming together of multiple scientific disciplines in an effort to understand how these highly connected systems function. The aim of this course will be to give an introduction to the study of networks, requiring as little background knowledge as possible. The course will begin with an analysis of some of the fundamental properties normally observed in real world networks, such as the small world property, high degrees of clustering and power law degree distributions. After reviewing required notions from game theory, we shall then apply these techniques to an analysis of the spread of behavioural change on networks, together with cascading effects and epidemic models. The final part of the course will be concerned with specific applications to the world wide web and page ranking.


20 hours of lectures and 10 hours of classes in the MT. 2 hours of lectures in the ST.

Formative coursework

Written answers to set problems will be expected on a weekly basis.

Indicative reading

(1) D. Easley, J. Kleinberg. Networks, crowds and markets, Cambridge University Press, 2010.  

(2) M. Newman. Networks: An Introduction, Oxford University Press, 2010.

(3) The Rise of the Network Society, The Information Age: Economy, Society and Culture, 2010 edition, Manuel Castells.


Exam (100%, duration: 2 hours) in the summer exam period.

Key facts

Department: Mathematics

Total students 2017/18: 19

Average class size 2017/18: 19

Capped 2017/18: No

Value: Half Unit

Guidelines for interpreting course guide information

PDAM skills

  • Self-management
  • Problem solving
  • Communication
  • Application of numeracy skills
  • Specialist skills