Re: [igraph] Choosing between different methods of detecting communities

[凌琛]

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 <address@hidden> 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 <address@hidden> 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 <address@hidden> wrote:
>>
>> On Sat, Sep 29, 2012 at 8:32 AM, 凌琛 <address@hidden> 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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--
Gabor Csardi <address@hidden>     MTA KFKI RMKI

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