A brief study on coevolution of Ising dynamics |
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Authors: | K B Hajra A K Chandra |
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Institution: | 1.Centre for Applied Mathematics and Computational Science,Saha Institute of Nuclear Physics,Kolkata,India;2.Theoretical Condensed Matter Physics Division,Saha Institute of Nuclear Physics,Kolkata,India |
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Abstract: | Community structure appears to be an intrinsic property of many complex real-world
networks. However, recent work shows that real-world networks reveal even more
sophisticated modules than classical cohesive (link-density) communities. In particular,
networks can also be naturally partitioned according to similar patterns of connectedness
among the nodes, revealing link-pattern communities. We here propose a propagation based
algorithm that can extract both link-density and link-pattern communities, without any
prior knowledge of the true structure. The algorithm was first validated on different
classes of synthetic benchmark networks with community structure, and also on random
networks. We have further applied the algorithm to different social, information,
technological and biological networks, where it indeed reveals meaningful (composites of)
link-density and link-pattern communities. The results thus seem to imply that, similarly
as link-density counterparts, link-pattern communities appear ubiquitous in nature and
design. |
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