[statnet_help] fragmented bipartite network...

[Martina Morris]

Hi Harald,

Thanks for reaching out, and for sending all the info.  That's really
helpful for us in answering your questions.

I haven't used the bipartite modeling options for a while, as we have
transitioned to using a different approach in our own research.  But based
on the simulated network from the model, I would guess that the bipartite
constraint is not operating properly -- and that's why you're getting a
very dense giant component.  Have you verified that there are no
cross-group ties in the simulated data?

I also think your model is probably not well-specified, in the sense that
it relies exclusively on dyad-dependent terms.  Models like this are known
to produce "near degenerate" networks -- that is, networks that are almost
complete, or almost empty, or artificially regular.  These kinds of models
would not produce the observed network that you have.  As Tom Kraft points
out, a better specification would probably include some of the
dyad-independent terms like "nodematch" to control homophily.

But I suspect you might actually get better results by taking the approach
we've been taking -- which uses offsets to control bipartite behavior
rather than bipartite network definitions.

I'll have more to say on this -- but am consulting with some of my
colleagues first :)

best,
Martina

agree with Tom Kraft's point

On Thu, Nov 30, 2023 at 10:00 AM Harald Waxenecker <waxenecker at fss.muni.cz>
wrote:


> Dear ‘statnet community’,

>

>

>

> Our research focuses on tie formation and elite cohesion, specifically

> examining interlocking directorates and kinship relations. The dependent

> bipartite business network comprises 6,902 individuals and 5,178 companies,

> exhibiting sparsity (density = 0.00012) and fragmentation with 4,455

> components, including 3,850 isolates in the first mode (persons). The

> attached documents contain descriptives and the component size distribution

> from the observed network.

>

>

>

> The fragmented structure is important, as other network layers, like

> kinship relations, are expected to contribute to the cohesion of this

> business network. We apply ERGM to model these processes, but we struggle

> to capture the fragmented structure of the observed network. The component

> size distribution of the simulated network differs significantly. In

> addition, the goodness-of-fit (GOF) for k-stars (in both modes) and

> geodesic distances (Inf) shows significant results. All these results are

> also attached.

>

>

>

> We've explored various options, including constraints, MCMC propositions,

> and simulated annealing, but haven't achieved success. Please, we would

> like to ask for your help to improve our model. Thank you!

>

>

>

> Kind regards,

>

> Harald

>

>

>

>

>

>

>

> ---

>

>

>

> *Harald Waxenecker *

>

> *Masaryk University | Faculty of social studies*

> Department of Environment Studies

> A: Jostova 10 | 602 00 Brno | Czech Republic

> E: waxenecker at fss.muni.cz

>

>

> _______________________________________________

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>

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