***** To join INSNA, visit http://www.insna.org ***** You are working with a 2-mode (bipartite) network for which you have attributes for the vertices in 1 mode. You would like to see how the attributes of the vertices in that mode are related to the distribution of vertices in the other mode. 

In my case, I am working with a 2-mode network in which the events are the winning Ads in an annual advertising contest in Japan and the participants are the Creators, members of the teams that produced the winning ads. Each Ad has several attributes (properties that map one-on-one with the Ads). Three of particular interest are Agency (the advertising agency that produced the ad), Medium (TV, radio, newspaper, magazine, poster, other), and Industry (12 industry categories into which the winning Ads are divided for judging). Exactly one Agency, Medium, or Industry attribute applies to each Ad.

Creators are related to Ads vis Roles. Since, however, a single Creator may receive credit for multiple Roles, and multiple Creators can receive credit for the same Role, these relationships are not one-to-one and cannot be treated as attributes.

Even so, it would be interesting to know how the distribution of Creators is affected by the the attributes of the Ads. 

The problem is that, while it is simple to construct a Pajek partitions reflecting the attributes for the Ads and use them to analyze the 1-mode Ad network projected from an original 2-mode AdCreator network, the 2-mode to 1-mode projection removes all of the creators. And since the partition has the same dimension as the projected 1-mode Ad network it cannot be used, as is, to analyze the original bipartite network with its different and larger dimension. 

Consider, for example, the 1986 Ad Creator network. This bipartite network contains a total of 1401 vertices: 480 Ads and 921 Creators. Each .clu Partition file contains attribute code for the 480 Ads. 

The command  Net>Transform>2 mode to 1 mode produces a 1-mode network of 480 Ads. The network and Partition files have exactly the same dimension=480. But the Creator vertices in the original 2-mode network have disappeared. But if I try to use the Partition files to analyze the original 1401-vertex 2-mode network, I get an error message, "Network and partition of equal size needed!" So, I look for a kludge, a trick that will get me past this error. Fortunately, there is one.

Partition>Create Constant Partition

allows me to create a partition of 921 vertices (921 because that is the number of Creators I need), all of which will have a single attribute, i.e., "Creator," indicated by whatever integer I choose for the constant. *I have to be careful here that this is not one of the integers already used to code attributes in the Ad attribute partitions. 

Partitions>Fuse Partitions

allows me to add this new constant partition to an attribute partition. 921+480=1401! I now have an attribute partition of the same dimension as the original 2-mode network. *Here I have to be careful that the order of the partitions to be used is correct, the original attribute partition in the first box, the new "Creator" constant partition in the second. 

When I use this technique to analyze the 1401-vertex AdsCreators network for 1986, the result of



Frequency distribution of cluster values:

   Cluster      Freq     Freq%   CumFreq  CumFreq% Representative
         0       335   23.9115       335   23.9115 AD1_86
         1        75    5.3533       410   29.2648 AD60_86
         2        70    4.9964       480   34.2612 AD11_86
        99       921   65.7388      1401  100.0000 Ito6226
       Sum      1401  100.0000

which, in this particular example, means that 921 Creators were involved in production of 480 Ads, with 75 ads produced by 1=Denstu (Japan's largest agency), 70 ads produced by 2=Hakuhodo (Japan's second largest agency) and 335 by 0=Other (some smaller agency). 

More importantly I now have a tool that lets me dig into this network in more detail, using Ad attributes to extract subnetworks of Creators for further analysis. But that is another trick.

If you find this helpful, or have suggestions or criticisms to offer, please drop me a line.


John McCreery
The Word Works, Ltd., Yokohama, JAPAN
Tel. +81-45-314-9324
[log in to unmask]
_____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.