Course pages 2016–17
Social and Technological Network Data Analytics
This module aims to introduce concepts of complex and social network analysis and its application to real social and technological networks.
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 a mixture of theory and modelling of networks but prevalently will be driven by large datasets from recent large and real complex networks including telephone networks, geographical networks, online social networks and human contact networks. The course is inclusive of a hands-on tutorial on manipulation of big data of networks with the purpose of analysis.
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.
- a report of at most 4000 words which analyzes a given data set (70%).
- a 10-minute presentation of the report (30%).
Easley, D. & Kleinberg, J. (2010). Networks, crowds, and markets:
reasoning about a highly connected world. Cambridge University Press.
Prepublication draft also available here
Newmann, M. (2010). Networks. Oxford University Press.
A full list of publications can be found on the course material web page.