Question

I designed a centrality metric to distinguish most connected nodes. The model is designed based on degree distribution of nodes. The first result implemented without edge weights show node I ranked over nodes B, D, E in figure 1 although they have the same number of connections.
The second result implemented with edge weights show that node I still ranked higher than nodes B, D, E in figure 2. I had expected that taking the weights into consideration will give more importance to nodes connected to edges of higher weights. But this is not the case.
My observation is that sometimes when nodes have the same number of connections, the model seems to penalize nodes connected to edges of higher weights and reward nodes connected to edges of lesser weights.
I would like to know if there is a natural occurrence of something like this in real world networks or is there something wrong with my model?

Answer 1

Answer:

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