A novel spreading framework using incremental clustering for viral marketing

Mining online social network has been a target for many recent studies in the literature. However, a limited have been aimed for the purpose of viral marketing. In this paper, a proposing of a novel spreading framework for viral marketing by using incremental clustering and activity network is presented. This framework ensures optimization in terms of cost and time by concentrating only on the most active users in online social network. Incremental clustering typically works at certifying that the viral marketing process is applied in the most updated network since many changes would occur in the networks especially in the node's connections. Generally, the framework divides the overall community into clusters each of which has its interest. In addition, it ensures the overlapping between clusters when users having more than one interest. Activity network, on the other hand, excludes the least active nodes or the ones with limited connections. This way will consume less cost and time comparing to cover all nodes (active and inactive).