Thanks for your comment. I don’t know of other packages specifically for weighted and directed networks. However, all but one function in tnet works on directed and weighted networks (the local clustering coefficient is not defined for directed networks; hence, only implemented for undirected ones).

Best,
Tore

thanks for your efforts.

Do you have any hints for analyzing weighted directed networks in R?

Best,
Majom

Yes, you’re right. That node id was an isolate and so the BC value should be 0.0.

Thanks so much for your helpful advice. I could not have come up with this myself.

Best Regards,
Fatemeh

Thank you for your email and data. This happens because node 1309 is an isolate, and is not kept when the as.tnet-function is automatically run on the edgelist (it deletes tie weights of 0). If you would like to have an isolate included, please put it into the middle of the edge id sequence. This process is shown here: http://toreopsahl.com/2010/03/20/closeness-centrality-in-networks-with-disconnected-components/

Hope this helps,
Tore

Thanks so much for your response. I tried the recent version as well but still received the same results (the last node is missing). I emailed you the link table and the code. Could you please have a look at them?

Many thanks for your help,
Fatemeh

Thanks for using tnet!

There has been an update of the tnet package recently. Could you run update.packages() to ensure you have version 3.0.7? If you are experiencing similar problems, email me with the code and data you are using.

Best,
Tore

I am interested to use the tnet package in order to calculate Betweenness Centrality for a weighted and undirected network. My network has 1309 nodes and 4229 links. I also add the reverse relationship between nodes to get the tnet to treat my network as an undirected one.

When I run the betweenness_W in R, it only gives me the BC value for the node 1 to 1308 and the last one (node id=1309) is missing. Do you have any idea what is the reason for this?

Kind Regards,
Fatemeh

I will keep in touch and follow your work to get in detail of this area. It would be great boost if you could guide me sir. (I know you are a busy person, still i ask you :-D) I just loved your work.

Thanks already,

Warm Regards,
Harsh

Thanks for using tnet!

The phi-function is the non-normalized weighted rich-club coefficient. The line starting with Er finds the ties within the prominent nodes. This should always be a list-object, so in tnet 3.1, sapply has been changed to lapply. The second line sum the tie weights of these ties.

Hope this helps,
Tore

(1) Er <- sapply(output[, "x"], function(a) which(net[, "rc"] > a))
(2) output[, "num"] <- unlist(lapply(Er, function(a) sum(net[a,"w"])))

It would be very helpful for me if I get several words from you about this.
Thank your time, and Best

Joon.