Long range community detection

Thomas Aynaud 1 Jean-Loup Guillaume 1
1 ComplexNetworks
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Complex networks can usually be divided in dense subnetworks called communities. In evolving networks, the usual way to detect communities is to find several partitions independently, one for each time step. However, this generally causes troubles when trying to track communities from one time step to the next. We propose here a new method to detect only one decomposition in communities that is good for (almost) every time step. We show that this unique partition can be computed with a modification of the Louvain method and that the loss of quality at each time step is generally low despite the constraint of global maximization. We also show that some specific modifications of the networks topology can be identified using this unique partition in the case of the Internet topology.
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Communication dans un congrès
LAWDN - Latin-American Workshop on Dynamic Networks, Nov 2010, Buenos Aires, Argentina. 4 p., 2010
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Thomas Aynaud, Jean-Loup Guillaume. Long range community detection. LAWDN - Latin-American Workshop on Dynamic Networks, Nov 2010, Buenos Aires, Argentina. 4 p., 2010. 〈inria-00531750〉

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