M2 S&E - Graph mining

M2 in Statistics and Econometrics, Toulouse School of Economics

Graph mining (2016-…, 10 hours)

Exam

Instructions and Dataset

Material

• Data: GOT and FB datasets (corresponding articles will be sent by email upon request) and the edge list of my facebook network and the vertices' names (initials)
• Introduction to graphs and networks: slides - worksheet 1
• Graph clustering: slides - worksheet 2
• Tests and random graphs: slides - worksheet 3

The R package igraph is needed for this class. To install it, write:

install.packages("igraph")

Other packages will be useful: ggplot2, RColorBrewer, microbenchmark, blockmodels and spdep.

Additional material

• Online course: Network Science, Albert-László Barabási;
• Software for graph visualization and mining: Gephi, Tulip and Cytoscape;
• Packages dedicated to graphs:
  • for Python: igraph, NetworkX and graph-tool;
  • for R: igraph, statnet, bipartite and tnet;
• Datasets: Mark Newman's web page, Standford Large Network Dataset Collection, KONECT collection and ICON.