Applying an Optimal Seed Selection Scheme Under a Progressive Model

In any social network, the most influential nodes are basically determined by either studying the topological nature of the network or the relationship between the two nodes in the network. Various existing seed selection schemes for progressive influence diffusion perform differently across different network structures. Thus, these seed selection schemes exhibit different results based on the network’s topological characteristics and therefore provide an approximate solution to seed selection. However, the advantage-of-seed-nodes method as presented in the paper [1] gives an optimal solution for selecting the seed nodes under a non-progressive diffusion process. In this paper, we apply this optimal scheme over the progressive diffusion process and investigate its influence spread under a progressive model. An experimental study over four different datasets shows that this method provides an efficient solution for seed selection even in a progressive diffusion model.