Dominant coverage for target users at the lowest cost under competitive propagation in social networks.

Multiple pieces of information disseminated in social networks can create a competitive environment where the influence of each message will be reduced. Thus, how to increase the influence under competitive propagation is significant for many applications such as product marketing and rumor suppression. In this paper, to make the dissemination targeted and maximize revenue, we propose the lowest cost problem to achieve dominant coverage for target users under competitive propagation(LC-CTU problem), using target user profiles and setting the objective to dominate coverage. To better model this scene, this paper proposes a competitive restricted propagation independent cascade model based on weights of attribute-generating edges(IC-CRA model), which adds competition, delay, and attributes to the basic independent cascade model. After proving that the LC-CTU problem under the IC-CRA model is NP-hard and the objective function is monotonic and submodular, the problem can be solved by a greedy algorithm. However, the greedy algorithm is time-consuming for large social networks. Thus, to improve the efficiency of the algorithm, we propose the lowest cost heuristic algorithm based on target users and restricted competition (LCH-TU algorithm), which uses the local influence update of each node for selecting the seed node. Finally, this paper demonstrates the effectiveness, efficiency, and scalability of the LCH-TU algorithm through extensive experiments on seven datasets, including real and artificial networks.