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Competitive influence maximization considering inactive nodes and community homophily
Knowledge-Based Systems ( IF 8.8 ) Pub Date : 2021-09-15 , DOI: 10.1016/j.knosys.2021.107497
Xiaoqin Xie 1 , Jiahui Li 1 , Yi Sheng 1 , Wei Wang 1 , Wu Yang 1
Affiliation  

Influence maximization has attracted much attention as a way to maximize influence spread through a social network. Most previous works focus on a non-competitive environment. But in the real world such as E-commerce, there are often multiple competitors at the same time to find influential users in order to advertise their similar products. So competitive influence maximization is introduced and some solutions are proposed. However, present studies have two limitations. First, they ignore the community homogeneity problem, which means that, information can spread easily among the individuals in the community, but it is hard to be diffused to other communities. Second, those latent users that are in inactive state are often considered to have no effects on other nodes. So most researches only consider those active nodes in terms of influence propagation. But in fact inactive nodes do have effects on the information propagation. In order to address above problems, in this paper we propose a competitive influence maximization method considering inactive nodes and community homophily. We first propose a new propagation model considering inactive nodes to simulate the information dissemination in a competitive environment, in which the inactive nodes are considered to have a weaker influence compared to the active ones. In order to break down the barriers of information dissemination between different communities, we propose a two-phase seed node selecting algorithm which has the minimum node number and maximum influence range. Our experiments on real world datasets verify the feasibility and accuracy of our proposed model and algorithm.



中文翻译:

考虑不活跃节点和社区同质性的竞争影响最大化

影响力最大化作为通过社交网络最大化影响力传播的一种方式引起了很多关注。以前的大多数作品都关注非竞争环境。但在电子商务等现实世界中,往往有多个竞争者同时寻找有影响力的用户,为他们的同类产品做广告。因此引入了竞争影响最大化并提出了一些解决方案。然而,目前的研究有两个局限性。首先,他们忽略了社区同质化问题,这意味着,信息可以很容易地在社区内的个人之间传播,但很难扩散到其他社区。其次,那些处于非活动状态的潜在用户通常被认为对其他节点没有影响。因此,大多数研究仅从影响传播的角度考虑那些活动节点。但实际上不活跃的节点确实对信息传播有影响。为了解决上述问题,本文提出了一种考虑不活跃节点和社区同质性的竞争影响力最大化方法。我们首先提出了一种考虑非活动节点的新传播模型来模拟竞争环境中的信息传播,其中与活动节点相比,非活动节点被认为具有较弱的影响。为了打破不同社区之间信息传播的障碍,我们提出了一种具有最小节点数和最大影响范围的两阶段种子节点选择算法。

更新日期:2021-10-02
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