Detecting modules in dense weighted networks with the Potts method

@inproceedings{Heimo2008DetectingMI,
  title={Detecting modules in dense weighted networks with the Potts method},
  author={Tapio Heimo and Jussi Kumpula and Kimmo Kaski and Jari Saramaki},
  year={2008}
}
  • Tapio Heimo, Jussi Kumpula, +1 author Jari Saramaki
  • Published 2008
  • Mathematics, Physics
  • We address the problem of multiresolution module detection in dense weighted networks, where the modular structure is encoded in the weights rather than topology. We discuss a weighted version of the q-state Potts method, which was originally introduced by Reichardt and Bornholdt. This weighted method can be directly applied to dense networks. We discuss the dependence of the resolution of the method on its tuning parameter and network properties, using sparse and dense weighted networks with… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-4 OF 4 REFERENCES

    Detecting modules in dense weighted networks with the Potts method

    • S Fortunato, M Barthélémy
    • Proc. Natl. Acad. Sci
    • 2007
    VIEW 2 EXCERPTS

    Scale-Free Networks

    VIEW 1 EXCERPT

    The structure and dynamics of networks (Princeton

    • E JNewmanM, A LBarabási, D JWatts
    • 2006
    VIEW 1 EXCERPT