I am dealing with three relation sets of the same actors I will explain ahead. These networks were built through Visone. Considering “Knime Network Plugin” resources/tools, I am asking for advice about which could be applied to improve this network analysis (actually, I have one objective question, but further advice will be welcome).
Follow attached the image of these networks; the different node size is related to the real size of the actors which are corporations.
For each set I measured (1) density and (2) correlation between degree and size:
a) Competition Network: the actors mentioned who are their competitors.
Correlation degree x size: 0.54 (p-value = 0.01)
b) Acting Network: the actors mentioned they know each other and exchange some general resources or information.
Correlation degree x size: 0.76 (p-value = 5.2)
c) Cooperation Network: the actors mentioned they effectively cooperate with each other in a “real” network structure.
Correlation degree x size: 0.45 (p-value = 0.03)
Considering correlation “degree x size”, it seems that in competition and cooperation networks, with moderate intensity, the bigger the actor, the bigger the likelihood of the competition and cooperation behaviour.
Considering density, it’s is clear that relations of competition are bigger than the others. Besides, it is suggestive that much of the cooperation network relations exist inside the other networks. I could see (not actually calculate) that even being competitors, same actors “act” or “cooperate” with each other (e.g. there are relations between actors B and T along the three networks; great part of actor relations in cooperation network exist inside competition network). So, is there any way to calculate the amount of these same actors who relations are (remain the same) in the different networks? I would like to find something like 80% of cooperative relations exist inside competition network.
As I told before, besides this question, any further advice/suggestion of analysis using Knime Network Plugin will be welcome!
Many thanks in advance,