Demaine, E.D. and Reidl, Felix and Rossmanith, P. and Villaamil Sánchez, F. and Sikdar, S. and Sullivan, B.D. (2019) Structural sparsity of complex networks: bounded expansion in random models and real-world graphs. Journal of Computer and System Sciences 105 , pp. 199-241. ISSN 0022-0000.
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Abstract
This research establishes that many real-world networks exhibit bounded expansion, a strong notion of structural sparsity, and demonstrates that it can be leveraged to design efficient algorithms for network analysis. Specifically, we give a new linear-time fpt algorithm for motif counting and linear time algorithms to compute localized variants of several centrality measures. To establish structural sparsity in real-world networks, we analyze several common network models regarding their structural sparsity. We show that, with high probability, (1) graphs sampled with a prescribed sparse degree sequence; (2) perturbed bounded-degree graphs; (3) stochastic block models with small probabilities; result in graphs of bounded expansion. In contrast, we show that the Kleinberg and the Barabási–Albert model have unbounded expansion. We support our findings with empirical measurements on a corpus of real-world networks.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | structural sparsity, bounded expansion, complex networks, random graphs, motif counting, centrality measures |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Felix Reidl |
| Date Deposited: | 03 Jun 2019 13:09 |
| Last Modified: | 09 Aug 2023 12:46 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/27714 |
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