python-3.xnetworkxgephicytoscape

Analyze networks which are not scale free


I am trying to analyze the graph constructed with networkx having around 7000 nodes. When I plot the degree distribution there are nodes that are far away from the fitted power law as shown in the attached plot. This means the network is not scale-free (to my understanding). I am trying to analyze this network by using various parameters such as Degree, clustering coefficient, betweenness centrality, and many others. Does analyzing such networks with these parameters is acceptable? I try to find some examples of analyzing networks that are not scale-free but no luck so far. Any suggestions and pointer for such examples would be really great. In addition, some differences in network characteristics of scale-free and non-scale free networks would be very helpful. Thanks in advance.enter image description here


Solution

  • 1. What type of model did you constructed? Did you use a data from a file?

    2. What do you want to check?

    Models such as Watts-Strogatz (https://en.wikipedia.org/wiki/Watts%E2%80%93Strogatz_model) is also no scale-free :

    'They do not account for the formation of hubs. Formally, the degree distribution of ER graphs converges to a Poisson distribution, rather than a power law observed in many real-world, scale-free networks.[3]'

    WS is a 'small-world' network. It is characterized by high clustering coefficient. Why you think you can't analyze it?