R help - Apr 2016 - Social Network Simulation

Dear all,

I am trying to simulate a series of networks that have characteristics
similar to real life social networks. Specifically I am interested in
networks that have (a) a reasonable degree of clustering (as measured by
the transitivity function in igraph) and (b) a reasonable degree of degree
polarization (as measured by the average degree of the top 10% nodes with
highest degree divided by the overall average degree).

Right now I am using two functions from irgaph (sample_pa and
sample_smallworld) but these are not ideal since they only allow me to vary
one of the two characteristics. Either the network has good clustering but
not enough polarization or the other way round.

I looked around and I found some network algorithms that solve the problem
(E.g., Jackson and Rogers, Meeting Strangers and Friends of Friends), but I
did not find their implemented in an R package. I also found the R package
NetSim which seems to be in this spirit, but I cannot get it to work.

Could anyone point me to an R library that I could check out? I do not care
much about the specific algorithm used as long as it allows me to vary
clustering and degree polarization in certain ranges.

Thanks,

Michael


Michael Haenlein
Professor of Marketing
ESCP Europe, Paris

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Dear Professor Haenlein,
Have you solved this issue yet? I found this eally interesting problem
I was wondering if it is possible to wrapper "objective function"
around igraph's 'sample_pa' and
'sample_smallworld'. If you have an example data set, I can have a look
at this.
Viele Gruesse aus London
Mehmet

On 16 April 2016 at 14:16, Michael Haenlein <haenlein at escpeurope.eu>
wrote:
> Dear all,
>
> I am trying to simulate a series of networks that have characteristics
> similar to real life social networks. Specifically I am interested in
> networks that have (a) a reasonable degree of clustering (as measured by
> the transitivity function in igraph) and (b) a reasonable degree of degree
> polarization (as measured by the average degree of the top 10% nodes with
> highest degree divided by the overall average degree).
>
> Right now I am using two functions from irgaph (sample_pa and
> sample_smallworld) but these are not ideal since they only allow me to vary
> one of the two characteristics. Either the network has good clustering but
> not enough polarization or the other way round.
>
> I looked around and I found some network algorithms that solve the problem
> (E.g., Jackson and Rogers, Meeting Strangers and Friends of Friends), but I
> did not find their implemented in an R package. I also found the R package
> NetSim which seems to be in this spirit, but I cannot get it to work.
>
> Could anyone point me to an R library that I could check out? I do not care
> much about the specific algorithm used as long as it allows me to vary
> clustering and degree polarization in certain ranges.
>
> Thanks,
>
> Michael
>
>
> Michael Haenlein
> Professor of Marketing
> ESCP Europe, Paris
>
>         [[alternative HTML version deleted]]
>
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