Hi Gabor,

If I want to omit edge weights and the graph is undirected, is it right to
set the arguments like this:

edge.betweenness.community(G, NULL, FALSE);

I am not sure, because the results are different from the same algorithm in
SNAP, which also implement Girvan-Newman's algorithm while only unweighted
version.

Thanks

Best Regards,
chen

On Tue, Oct 2, 2012 at 9:27 PM, Gábor Csárdi <[email protected]> wrote:

> Hi,
>
> from ?edge.betweenness.community:
>
> ...
>  weights: The edge weights. Supply ‘NULL’ to omit edge weights. By
>           default the ‘‘weight’’ edge attribute is used, if it is
>           present.
> ...
>
> So, yes, if the edge weights are assigned as the 'weight' attribute,
> then you don't need to supply them explicitly.
>
> Gabor
>
> On Tue, Oct 2, 2012 at 6:27 AM, 凌琛 <[email protected]> wrote:
> > Hi Gabor,
> >
> > If I want to use the weighted edge betweenness community detection
> algorithm
> > in R, is it enough to just use
> >
> > edge.betweenness.community(G)?
> >
> > Namely, it is no need to add arguments about edge weights in the graph.
> > Thanks.
> >
> > Regards,
> >
> > chen
> >
> > On Sat, Sep 29, 2012 at 9:06 PM, Gábor Csárdi <[email protected]>
> wrote:
> >>
> >> On Sat, Sep 29, 2012 at 8:32 AM, 凌琛 <[email protected]> wrote:
> >> > OK, so that if I use similarity of nodes as edge weights, I need to
> >> > transform the weights (i.e., inverse) for detecting community.
> >> > is that right?
> >>
> >> I think so, because when you calculate shortest paths, you want edge
> >> weights to represent distances.
> >>
> >> Gabor
> >>
> >> [...]
> >>
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> >
> >
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>
>
>
> --
> Gabor Csardi <[email protected]>     MTA KFKI RMKI
>
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