Computer Laboratory

Course pages 2014–15

Social and Technological Network Analysis

Principal lecturer: Dr Cecilia Mascolo
Taken by: MPhil ACS, Part III
Code: L109
Hours: 16
Class limit: 18 students
Prerequisites: An undergraduate course on probability

Aims

This module aims to introduce concepts of complex and social network analysis and its application to real social and technological networks.

Syllabus

The course will consist of sixteen lectures covering the following material:

  • Introduction to Complex Networks and Random Graphs
  • Small World and Weak ties
  • Network Centrality and Applications
  • Communities, Overlapping Communities and Community Detection
  • Structure of the Web, Search and Power Laws
  • Network Robustness and Applications
  • Cascades and Behaviour Influence
  • Epidemic Spreading
  • Epidemic Spreading and Information Cascades Examples
  • Temporal Network Analysis
  • Spatial Network Analysis
  • Challenges in the Analysis of Big Data and Network Analysis Tools

The lectures will contain various examples from recent analysis of large and real social networks including telephone networks, online social networks and human contact networks, as well as a hands-on tutorial on manipulation of big data of social networks with the purpose of analysis.

Objectives

On completion of this module students should be familiar with the most common metrics and techniques of complex network analysis and classification, as well as the most recent applications of these techniques in the area of social and technological networks as well as the tools to handle big networks and complex measures.

Assessment

  • a critical evaluation of a research paper of at most 1,500 words (30% of final mark).
  • a report of at most 2,500 words which analyzes a given data set (50%).
  • a 10-minute presentation of the report (20%).

Recommended reading

Easley, D. & Kleinberg, J. (2010). Networks, crowds, and markets: reasoning about a highly connected world. Cambridge University Press.
Newmann, M. (2010). Networks. Oxford University Press.

A full list of publications can be found on the course material web page.