Synthetic Graph Datasets
This page contains a sample of the synthetic datasets used in the evaluations in the paper:
Scaling Community Finding Algorithms to Work for Large Networks Through Problem Decomposition
A. Narasimhamurthy, D. Greene, N. Hurley, and P. Cunningham (2008)
These datasets are designed to examine how community finding techniques scale to large, sparse graphs, approaching the size of those occurring in real-world problems such as measuring churn in mobile subscriber networks.
Download
Datasets of different sizes are available in the archives below:
Archive containing full set of 1000-node graphs
Archive containing sample set of ten 2000-node graphs
Archive containing sample set of ten 5000-node graphs
Archive containing sample set of ten 10000-node graphs
Archive containing sample set of ten 50000-node graphs
Archive containing sample set of ten 100000-node graphs
Contact
For further information please contact Derek Greene.