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Social Networks and Graph Analysis

This module introduces students to the theory and techniques of graph analysis.

By taking this module, you will have an opportunity to master the theory and practice of graph analysis and social data analysis. You will be shown how to gather datasets from public social networking platforms. You will learn how to convert social network data into graph representations and then apply typical algorithms to analyse the structure of the graph. You will visualise graphs and assess data flow and influence between nodes in the graph.

Topics covered

  • Directed and undirected graphs
  • Paths, including Hamiltonian and Eulerian paths
  • Distance and shortest path
  • Complexity theory
  • The PageRank algorithm
  • Directed acyclic graphs
  • Retrieving social network data
  • Generating graphs from social network data
  • Betweeness centrality in social networks
  • Visualisation of networks

Credits

15 (150 hours)

Assessment

  • Summative coursework (30%)
  • Written examination (70%)