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2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (2012)
Istanbul Turkey
Aug. 26, 2012 to Aug. 29, 2012
ISBN: 978-1-4673-2497-7
pp: 274-281
F. Reid , Complex Adaptive Syst. Lab., Univ. Coll. Dublin, Dublin, Ireland
A. McDaid , Complex Adaptive Syst. Lab., Univ. Coll. Dublin, Dublin, Ireland
N. Hurley , Complex Adaptive Syst. Lab., Univ. Coll. Dublin, Dublin, Ireland
ABSTRACT
K-clique percolation is an overlapping community finding algorithm which extracts particular structures, comprised of overlapping cliques, from complex networks. While it is conceptually straightforward, and can be elegantly expressed using clique graphs, certain aspects of k-clique percolation are computationally challenging in practice. In this paper we investigate aspects of empirical social networks, such as the large numbers of overlapping maximal cliques contained within them, that make clique percolation, and clique graph representations, computationally expensive. We motivate a simple algorithm to conduct clique percolation, and investigate its performance compared to current best-in-class algorithms. We present improvements to this algorithm, which allow us to perform k-clique percolation on much larger empirical datasets. Our approaches perform much better than existing algorithms on networks exhibiting pervasively overlapping community structure, especially for higher values of k. However, clique percolation remains a hard computational problem, current algorithms still scale worse than some other overlapping community finding algorithms.
INDEX TERMS
Communities, Complex networks, Educational institutions, Facebook, Benchmark testing, Adaptive systems, Scalability, Percolation, Complex Networks, Social Networks, Network Analysis
CITATION

N. Hurley, A. McDaid and F. Reid, "Percolation Computation in Complex Networks," 2012 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining(ASONAM), Istanbul, 2012, pp. 274-281.
doi:10.1109/ASONAM.2012.54
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