MSP-N: Multiple selection procedure with ‘N’ possible growth mechanisms

Network modeling is a challenging task due to non-trivial evolution dynamics. We introduce multiple-selection-procedure with ‘N’ possible growth mechanisms (MSP-N). In MSP-N, an incoming node chooses a single option among N available options to link to pre-existing nodes. Some of the potential options, in case of social networks, can be standard preferential or random attachment and node aging or fitness. In this paper, we discuss a specific case, MSP-2, and shows its efficacy in reconstructing several non-trivial characteristic properties of social networks, including networks with power-law degree distribution, power-law with an exponential decay (exponential cut-off), and exponential degree distributions. We evaluate the proposed evolution mechanism over two real-world networks and observe that the generated networks highly resembles the degree distribution of the real-world networks. Besides, several other network properties such as high clustering and triangle count, low spectral radius, and community structure, of the generated networks are significantly closer to the real-world networks.