Complex networks have the number of common features, but is there an outstanding feature of each complex network which does not exist in the rest? For instance, the Rich-club property, there is more to be seen in the brain networks.Can we say each of them has a unique feature?
Depending on the class of these complex networks. Scale-free networks for example share a common property of having a degree distribution that follows power-law distribution.
Regarding the rich-club coefficient: From my research on social crowdsourcing communities (SCCs), I found that their networks are scale-free and have small Rich-club coefficients, contrary to social networks who are scale-free and have higher rich-club coefficients.
The small rich-club coefficient makes makes sense in SSc because they have moderators who tend to very active and highly popular; yet rarely associate with each other (through following or befriending) or interact with each other in the SCC. This is because of the nature of their duties that makes it useless for them to associate with one another. In my case specifically, moderators are hired by the same SCC so they work off of the same physical space and therefore have direct access to each other off-line, which limits the need for on-line association.
In the spreader detection research field, so many centrality measures have been proposed. Different centrality measures make use of diverse topological features of the complex networks to rank the spreading ability of the nodes. Some like degree centrality considers the first-step neighborhood of the node. Some like LC takes into account up to the next nearest neighbors of the node. Other centralities like betweenness and closeness use the obtained information based on the shortest path between nodes. Some like k -shell emphasize on the node location in the graph, and so on. The diversity of networks in the aspect of structural properties causes the fact that “centrality measures have different performances in networks with different structures”. Meaning that the performance of (PDF) Effect of rich-club on diffusion in complex networks.
I am not sure I understand what you are exactly looking for. But according to my understanding to your question, assume two networks; co-authorship network and political network and both have scale-free features. Network measurements are applicable to both of them but each reflects different fact since the nature and the purpose of each network is different from the other one. If you go to the distinguished works of Barabasi you find an answer to every single question you have.
Dear prof.luciano, thank you very much for your explanation. It was so helpful for me.
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