Community Detection in Complex Networks using Genetic Algorithm

Details Community Detection in Complex Networks using Genetic Algorithm Community Detection in Complex Networks using Genetic Algorithm

2006-04-18

arxiv.org/abs/cond-mat/0604419v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

submitted to Physical Review,waiting for response; 6 pages. See also: Tasgin, M.,"Community Detection Model using Genetic Algo

Scientific paper

Community structure identification has been an important research topic in complex networks and there has been many algorithms proposed so far to detect community structures in complex networks, where most of the algorithms are not suitable for very large networks because of their time-complexity. Genetic algorithm for detecting communities in complex networks, which is based on optimizing network modularity using genetic algorithm, is presented here. It is scalable to very large networks and does not need any priori knowledge about number of communities or any threshold value. It has O(e) time-complexity where e is the number of edges in the network. Its accuracy is tested with the known Zachary Karate Club and College Football datasets. Enron e-mail dataset is used for scalability test.

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