Kind regards,

Thi. ]]>

Hi Thi,

Just swap the columns around and compute the two-mode centrality measure!

Good luck!

Tore

Thank you for the package and all of the resources made available on this website. I have found them extremely useful as I am a beginner when it comes to R and network analysis. In your discussion above, the centrality measures are at individual level. What if I want to calculate centrality at mode level. For example, instead of measuring the centrality of each director sitting on a board of a company, I want to measure the centrality of each board. Is this possible?

Best regards,

Thi.

]]>Many thanks, Tore!

I already did the computations and compared the different projection methods. This way of applying the Newman method is not exactly what I’d like to reflect but it’s better than the other methods.

I’m working with groups and members of meetup.com. Positive RSVP’s by members to events of a group make up the weights. I’m seeing the groups as sources for information and innovation and perform community detection to identify clusters of groups. Ideally, the projection accounts for the higher level of interaction and quality of information exchange among smaller groups. I assume by projecting onto the groups this has similar results (probably due to a long-tail effect), but rather reflects concepts of exclusivity and loyalty of groups’ members.

Hi Judith,

I am not sure. The method would basically assume that each participant contributes 1 to a meeting’s sum of tie weights. If a woman attended just two meetings, 1 would be added to their tie’s weight. If another woman attended 3 meetings, each tie between the three meetings would be increased with 0.5. I think it does depend on what your research question is.

From an implementation perspective, you can just swap the columns of the network object before projecting (e.g., net2 <- net[,c(2,1,3)]).

Best,

Tore

If I would be interested in the meeting groups (as primary notes) rather than the women does the Newman projection method still make sense? ]]>

I have sent my data set on your email.

Kind regards,

]]>Hi Abdul,

There is no such limitation. Please send me an email with the data and code, and I will have a look at it.

Tore

]]>Why in 2-mode networks the betweenness score is 0. What can be a reason for this limitation. I’m working on 2-mode network and I have observed such type of results in my network.

Thanks

]]>Hi Krishna,

The best way is simply to use a reversed edgelist. For example, you can use the command degree_tm(net[,2:1]) for a binary two-mode network called net, and degree_tm(net[,c(2,1,3)]) for a weighted two-mode network.

Hope this helps,

Tore