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Vaughan,

As I indicated to you, this method is described by Duncan Watts in his 1999 AJS paper. More specicially, you don't need to generate random networks to know their path length or clustering coefficient. The approximations for path length can be computed as follows:

Lrandom=ln(n)/ln(k) where n is the number of nodes and k is a number of ties in the network

Approximation for clustering coefficient is computed as
Crandom=k/n

Again, for more comprehensive review, I suggest you read:
Watts, D. 1999 "Networks, dynamics and the small world phenomenon." American Journal of Sociology, 105: 493-527

Andrew

        -----Original Message-----
        From: Vaughan [mailto:[log in to unmask]]
        Sent: Tue 11/18/2003 6:03 AM
        To: [log in to unmask]
        Cc:
        Subject: Random network generation



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        Hello everyone,

        I would like to generate a random network, with a similar number of ndoes
        and connection to the network I have created from field data, to compare the
        distance and clustering co-efficient of each. Not unlike the the method in
        http://arxiv.org/pdf/cond-mat/0307439

        My network created from field data has no isolated nodes. However, when I
        ask Pajek to create a network with the same number of nodes and connections
        I get plenty of isolates, which apparently will not make a valid clustering
        co-efficient or distance comparison.

        Andrew Shipilov kindly suggested to my that it is possible to generate
        distance and clustering coefficients purely from knowing the number of nodes
        and connections I wish to use, although I am having trouble tracking down
        this method.

        Can anyone suggest a way of either generating a random network with a
        specified number of nodes and connections that has no isolates or doing the
        above calculation ?

        Many thanks,
        Vaughan Bell

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