1MSc student, School of Electrical and Computer Engineering, University of Tehran
2University of Tehran
3MSc student, faculty of electrical and computer engineering university of tehran
Maximizing product adoption in viral marketing is the task of choosing a small set of seed nodes in a social network so that by their approval to adopt the product, they influence others and lead to large number of adoptions. In this paper, a special case is investigated in which nodes, because of their potential profitability, are not of the same importance to the sales manager. We assign importance weight values to the communities of nodes that are most likely to share the same characteristics and are of the same importance to the seeker of seed nodes. We define MPAC, Maximizing Product Adoption considering the profitability of Communities that is the problem of selecting seed nodes such that the spread of influence results in maximum profit. This is done by activating nodes residing within weighted communities which worth the cost of activating. Three algorithms are proposed to solve MPAC. Our empirical studies on an online social network consisted of 23628 nodes show that one of them outperforms the others by the overall profits gained and as more as the weighting method assigns larger values to small communities, the proposed algorithm performs better.
product adoption, influence maximization, viral marketing, customer profitability, community detection