Discussion:
[igraph] graphs with varying centralization
John Erwin Banez
2018-04-02 06:10:48 UTC
Permalink
How do I generate several igraphs with varying graph level centralization?
I am familiar with sample_(...), that variations of 'sample_' allow me to
generate graphs GIVEN a MODEL....but not given graph level centralization.

I would like to have for example:

graph_1 <- centralization=.50
graph_2 <- centralization=.30

.

.

.

graph_n <- centralization=.00
--
John Erwin Bañez
Assistant Professor
College of Social Work and Community Development
University of the Philippines, Diliman
Szabolcs Horvát
2018-04-02 09:48:18 UTC
Permalink
If you want uniform sampling, then this is a research-level problem (not a
technical one). If you don't, I wonder what conclusion you could draw from
the results.
Post by John Erwin Banez
How do I generate several igraphs with varying graph level centralization?
I am familiar with sample_(...), that variations of 'sample_' allow me to
generate graphs GIVEN a MODEL....but not given graph level centralization.
graph_1 <- centralization=.50
graph_2 <- centralization=.30
.
.
.
graph_n <- centralization=.00
--
John Erwin Bañez
Assistant Professor
College of Social Work and Community Development
University of the Philippines, Diliman
_______________________________________________
igraph-help mailing list
https://lists.nongnu.org/mailman/listinfo/igraph-help
John Erwin Banez
2018-04-03 00:28:01 UTC
Permalink
I am trying to test robustness of a method I am trying to develop. Having
igraphs with varied centrality helps.
Post by Szabolcs Horvát
If you want uniform sampling, then this is a research-level problem (not a
technical one). If you don't, I wonder what conclusion you could draw from
the results.
Post by John Erwin Banez
How do I generate several igraphs with varying graph level
centralization? I am familiar with sample_(...), that variations of
'sample_' allow me to generate graphs GIVEN a MODEL....but not given graph
level centralization.
graph_1 <- centralization=.50
graph_2 <- centralization=.30
.
.
.
graph_n <- centralization=.00
--
John Erwin Bañez
Assistant Professor
College of Social Work and Community Development
University of the Philippines, Diliman
_______________________________________________
igraph-help mailing list
https://lists.nongnu.org/mailman/listinfo/igraph-help
_______________________________________________
igraph-help mailing list
https://lists.nongnu.org/mailman/listinfo/igraph-help
--
John Erwin Bañez
Assistant Professor
College of Social Work and Community Development
University of the Philippines, Diliman
Szabolcs Horvát
2018-04-03 08:35:10 UTC
Permalink
It is usually easy enough to create one or a few instances of a graph with
a certain property. E.g., you can make an educated guess about which model
already in igraph will produce a certain property, then vary its
parameters. Or smoothly interpolate between the adjacency matrices of two
graphs having different values of a property. E.g. a star graph will have
betweenness centralization of nearly 1, a cycle graph nearly 0.

Will the graphs you obtain this way be representative of most graphs with
the same 'centralization' (or other property) value? Probably not. That
will also be the case if you choose more "random looking" graphs as
starting points, such as one from a preferential attachment model and a
random regular graph. Therein lies the problem with using any arbitrary
graph with a property instead of sampling them uniformly.
Post by John Erwin Banez
I am trying to test robustness of a method I am trying to develop. Having
igraphs with varied centrality helps.
Post by Szabolcs Horvát
If you want uniform sampling, then this is a research-level problem (not
a technical one). If you don't, I wonder what conclusion you could draw
from the results.
Post by John Erwin Banez
How do I generate several igraphs with varying graph level
centralization? I am familiar with sample_(...), that variations of
'sample_' allow me to generate graphs GIVEN a MODEL....but not given graph
level centralization.
graph_1 <- centralization=.50
graph_2 <- centralization=.30
.
.
.
graph_n <- centralization=.00
--
John Erwin Bañez
Assistant Professor
College of Social Work and Community Development
University of the Philippines, Diliman
_______________________________________________
igraph-help mailing list
https://lists.nongnu.org/mailman/listinfo/igraph-help
_______________________________________________
igraph-help mailing list
https://lists.nongnu.org/mailman/listinfo/igraph-help
--
John Erwin Bañez
Assistant Professor
College of Social Work and Community Development
University of the Philippines, Diliman
_______________________________________________
igraph-help mailing list
https://lists.nongnu.org/mailman/listinfo/igraph-help
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