移动社会网络中基于全局信任模型的用户影响力计算  

Global Trust Model Based Users’Influence Calculation in Mobile Social Networks

作　　者：徐振宇 张欣欣 许力[1,2] XU Zhen-Yu;ZHANG Xin-Xin;XU Li(College of Computer and Cyber Security,Fujian Normal University,Fuzhou 350117,China;Fujian Provincial Key Laboratory of Network Security and Cryptology,Fuzhou 350007,China)

机构地区：[1]福建师范大学计算机与网络空间安全学院,福州350117 [2]福建省网络安全与密码技术重点实验室,福州350007

出　　处：《计算机系统应用》2022年第3期302-309,共8页Computer Systems & Applications

基　　金：国家自然科学基金(U1905211,61771140,61702100,61702103);企事业合作项目(DH-1565,DH-1412)。

摘　　要：针对现有算法和模型对于网络中用户影响力计算大多只考虑拓扑结构和贪心算法而较少考虑真实社会网络中信任度对于节点影响力的重要性这一问题,该文提出一种全局信任模型(global trust model,GTM)用于评估节点的影响力.首先计算节点与邻居节点间的信任关系作为局部信任度,其次利用Beta信誉模型在节点局部信任度的基础上得到全局信任度,最后根据节点的全局信任度评估节点的影响力大小.在真实的网络数据集上对该模型与经典影响力算法进行实验对比,结果表明,该文提出的方法不仅具有更低的时间复杂度,并且在保证节点可信度与精确度的同时也具有良好的影响传播能力.To address the problem that most existing algorithms and models for calculating user influence in networks only consider topology and greedy algorithms while rarely take into account the importance of trust degree on node influence,this study proposes a global trust model(GTM)for evaluating node influence.The trust relationships of a node with its neighbor nodes are calculated as the local trust degrees.Then,the Beta reputation model is used to obtain the global trust degree through the local trust degrees of the node.Finally,the node influence is evaluated according to the global trust degree of the node.Experiments are conducted on real network datasets to compare this model with classical influence algorithms.The experimental results show that the proposed method not only has lower time complexity but also demonstrates a favorable influence propagation ability in addition to ensuring node trustworthiness and accuracy.

关 键 词：全局信任模型 节点信任度 影响力 移动社会网络 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O157.5[自动化与计算机技术—控制科学与工程]