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NW_WCC: Stata module to calculate Weighted Clustering Coefficients (WCC) in Complex Direct Networks

Author

Listed:
  • Charlie Joyez

    (Paris-Dauphine University)

Programming Language

Stata

Abstract

nw_wcc calculates the clustering coefficient of each node i among a network, following the pattern indicated in option and saves the result as a Stata variable specific to the pattern and the binary or weighted dimension. At least one pattern should be indicated, if not, the pattern all is the default. By default, weights are not normalized as in Fagiolo, Phys. Rev. E (2007), because they are assumed to be in the range [0,1]. Without the normalized option, the clustering coefficients are not scale invariant. The normalize option rescale all weights into a [0;1] range, and makes the clustering coefficient scale invariant. The default normalization procedure (also accessible by typing normalized(max)) divides all weights (w) by max(w) (See discussion in Saramaki et al. (2007)). Option normalize(sum) normalizes (w) by Sum(w), where Sum(w) is the sum of all the network weights.

Suggested Citation

  • Charlie Joyez, 2017. "NW_WCC: Stata module to calculate Weighted Clustering Coefficients (WCC) in Complex Direct Networks," Statistical Software Components S458305, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:s458305
    Note: This module should be installed from within Stata by typing "ssc install nw_wcc". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/n/nw_wcc.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/n/nw_wcc.sthlp
    File Function: help file
    Download Restriction: no
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    Cited by:

    1. Nadia von Jacobi & Vito Amendolagine, 2021. "What Feeds on What? Networks of Interdependencies between Culture and Institutions," DEM Working Papers 2021/13, Department of Economics and Management.

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