Diffusing information for mobile social networks under consideration of dynamic influence. (April 2017) - Jing, Dong; Liu, Ting
As the developments of new techniques, mobile social networks have been built wildly. To obtain and spread information over mobile social networks efficiently, the influence maximization problem is to find a seed nodes set with limited size such that it can influence as many nodes as possible. Previous works ignore the dynamic influence phenomenon of diffusing information on mobile social networks. In this article, we propose a new model to express the procedure of diffusing information under the existence of dynamic influence. Theoretical analysis shows that the influence maximization problem under new model is non-deterministic polynomial-time hard, and efficient approximation algorithm is proposed. Experimental studies on real data sets show that the new model can process dynamic influence well in the diffusing information procedure, and the proposed algorithms can solve the influence maximization problem on new model efficiently.