Maximizing influence of viral marketing via evolutionary user selection

Viral marketing, which uses the “word of mouth” marketing technique over virtual networks, relies on the selection of a small subset of most influential users in the network for efficient marketing. Nonetheless, most existing viral marketing techniques ignore the dynamic nature of the virtual network. In this paper, we develop a novel framework that exploits the temporal dynamics of the network to select an optimal subset of users that maximize the marketing influence over the network.