In this paper we introduce a fuzzy propagation model to deal with the influence maximization (IM) problem. The IM problem for the most of existing propagation model is NP-hard. Here, we model social networks as fuzzy directed graphs to propose an application-oriented propagation process. To this aim, we investigate an interesting relationship between zero forcing set concept in graphs and IM problem in social networks. In spite of its attractive theory, its implementation is not efficient in the real world. Thus, we improve the fuzzy zero forcing set concept and suggest our fuzzy propagation model, simultaneously. Moreover, we present a polynomial time complexity algorithm to solve IM problems under the proposed propagation process. In particular, we consider a propagation parameter to control the size of the seed set and its coverage. Also, experimental results on some real world social networks show that the propagation model finds optimal and flexible seed set.

在本文中，我们引入了一种模糊传播模型来处理影响最大化 (IM) 问题。大多数现有传播模型的 IM 问题是 NP-hard。在这里，我们将社交网络建模为模糊有向图，以提出面向应用的传播过程。为此，我们研究了图形中的迫零集概念与社交网络中的 IM 问题之间的有趣关系。尽管其理论很有吸引力，但在现实世界中其实施效率不高。因此，我们改进了模糊逼零集的概念并同时提出了我们的模糊传播模型。此外，我们提出了一种多项式时间复杂度算法来解决所提出的传播过程下的 IM 问题。特别是，我们考虑传播参数来控制种子集的大小及其覆盖范围。还，