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***** To join INSNA, visit http://www.insna.org ***** Using Pajek to dissect my 2-mode network data on Japanese advertising creatives and the teams that produce winning ads, I make a  now-conventional move—projecting two 1-mode networks. From each of the 1-mode networks, I extract the giant component. Having extracted the giant component I have Pajek compute the normalized degree, closeness, betweenness and eigenvalue centrality (hubs and authorities) vectors. I then use the Vectors>Info command to examine the Spearman rank correlations between the four vectors. I discover a curious phenomenon. In the case of the 1-mode network of individual creators, the highest correlation (.7~.8) is between normalized degree and betweenness. In the case of the 1-mode network of teams, however, the highest correlation (again in the .7~.8 range) is between normalized degree and closeness. 


Has anyone else encountered this phenomenon? Is this a common and/or mathematically predictable result? If so, please tell me how it works or where to look for an explanation.

John

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John McCreery
The Word Works, Ltd., Yokohama, JAPAN
Tel. +81-45-314-9324
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http://www.wordworks.jp/
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