  Networks are everywhere and their many types, including social networks, the
Internet, food webs etc., have been studied for the last few decades. However,
in real-world networks, it's hard to find examples that can be easily
comparable, i.e. have the same density or even number of nodes and edges. We
propose a flexible and extensible NetSim framework to understand how properties
in different types of networks change with varying number of edges and
vertices. Our approach enables to simulate three classical network models
(random, small-world and scale-free) with easily adjustable model parameters
and network size. To be able to compare different networks, for a single
experimental setup we kept the number of edges and vertices fixed across the
models. To understand how they change depending on the number of nodes and
edges we ran over 30,000 simulations and analysed different network
characteristics that cannot be derived analytically. Two of the main findings
from the analysis are that the average shortest path does not change with the
density of the scale-free network but changes for small-world and random
networks; the apparent difference in mean betweenness centrality of the
scale-free network compared with random and small-world networks.
