The purpose of influence maximization problem is to select a small seed set to maximize the number of nodes influenced by the seed set. For viral marketing, the problem of influence maximization plays a vital role. Current works mainly focus on the unsigned social networks, which include only positive relationship between users. However, the influence maximization in the signed social networks including positive and negative relationships between users is still a challenging issue. Moreover, the existing works pay more attention to the positive influence. Therefore, this paper first analyzes the positive maximization influence in the signed social networks. The purpose of this problem is to select the seed set with the most positive influence in the signed social networks. Afterwards, this paper proposes a model that incorporates the state of node, the preference of individual and polarity relationship, called Independent Cascade with the Negative and Polarity (ICWNP) propagation model. On the basis of the ICWNP model, this paper proposes a Greedy with ICWNP algorithm. Finally, on four real social networks, experimental results manifest that the proposed algorithm has higher accuracy and efficiency than the related methods.

中文翻译：

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考虑极性关系和传播概率的签名社交网络中的积极影响最大化

影响最大化问题的目的是选择一个小的种子集来最大化受种子集影响的节点数。对于病毒式营销，影响力最大化问题起着至关重要的作用。目前的工作主要集中在未签名的社交网络上，其中仅包含用户之间的正向关系。然而，包括用户之间的正负关系在内的签名社交网络中的影响力最大化仍然是一个具有挑战性的问题。此外，现有作品更注重积极影响。因此，本文首先分析了签名社交网络中的积极最大化影响。这个问题的目的是选择签名社交网络中影响最大的种子集。之后，本文提出了一个包含节点状态的模型，个体和极性关系的偏好，称为具有负和极性（ICWNP）传播模型的独立级联。本文在ICWNP模型的基础上，提出了一种带有ICWNP的Greedy算法。最后，在四个真实的社交网络上，实验结果表明，该算法比相关方法具有更高的准确性和效率。