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Divisive algorithms are widely used for community detection. A common strategy of divisive algorithms is to remove the external links which connect different communities so that communities get disconnected from each other. Divisive algorithms have been investigated for several decades but some challenges remain unsolved: (1) how to efficiently identify external links, (2) how to efficiently remove external links, and (3) how to end a divisive algorithm with no help of predefined parameters or community definitions. To overcome these challenges, we introduced a concept of the weak link and autonomous division. The implementation of the proposed divisive algorithm adopts a new link-break strategy similar to a tug-of-war contest, where communities act as contestants and weak links act as breakable ropes. Empirical evaluations on artificial and real-world networks show that the proposed algorithm achieves a better accuracy-efficiency trade-off than some of the latest divisive algorithms.

An Autonomous Divisive Algorithm for Community Detection Based on Weak Link and Link-Break Strategy