Towards Democratic Group Detection in Complex Networks
To detect groups in networks is an interesting problem with applications in social and security analysis. Many large networks lack a global community organization. In these cases, traditional partitioning algorithms fail to detect a hidden modular structure, assuming a global modular organization. We define a prototype for a simple local-first approach to community discovery, namely the democratic vote of each node for the communities in its ego neighborhood. We create a preliminary test of this intuition against the state-of-the-art community discovery methods, and find that our new method outperforms them in the quality of the obtained groups, evaluated using metadata of two real world networks. We give also the intuition of the incremental nature and the limited time complexity of the proposed algorithm.
KeywordsCrime Prevention Label Propagation Real World Network Community Quality Quantitative Attribute
Unable to display preview. Download preview PDF.
- 5.Goyal, A., On, B.-W., Bonchi, F., Lakshmanan, L.V.S.: Gurumine: A pattern mining system for discovering leaders and tribes. In: International Conference on Data Engineering, pp. 1471–1474 (2009)Google Scholar
- 6.Henderson, K., Eliassi-Rad, T., Papadimitriou, S., Faloutsos, C.: Hcdf: A hybrid community discovery framework. In: SDM, pp. 754–765 (2010)Google Scholar
- 8.Raghavan, U.N., Albert, R., Kumara, S.: Near linear time algorithm to detect community structures in large-scale networks. Physical Review E (2007)Google Scholar
- 10.Shen, H.-W., Cheng, X.-Q., Guo, J.-F.: Quantifying and identifying the overlapping community structure in networks. J. Stat. Mech. (2009)Google Scholar
- 11.Yonas, M.A., Borrebach, J.D., Burke, J.G., Brown, S.T., Philp, K.D., Burke, D.S., Grefenstette, J.J.: Dynamic Simulation of Community Crime and Crime-Reporting Behavior. In: Salerno, J., Yang, S.J., Nau, D., Chai, S.-K. (eds.) SBP 2011. LNCS, vol. 6589, pp. 97–104. Springer, Heidelberg (2011)CrossRefGoogle Scholar