计算机与现代化 ›› 2021, Vol. 0 ›› Issue (09): 37-42.

• 算法分析与设计 • 上一篇    下一篇

融合客观赋权法的社交网络谣言源检测算法

  

  1. (新疆师范大学计算机科学技术学院,新疆乌鲁木齐830054)
  • 出版日期:2021-09-14 发布日期:2021-09-14
  • 作者简介:周中月(1993—),男,山东菏泽人,硕士研究生,研究方向:自然语言处理,社交网络分析,E-mail: 976163484@qq.com; 通信作者:张海军(1973—),男,吉林四平人,教授,博士,研究方向:自然语言处理,信息抽取,人工智能,E-mail: zhjlp@163.com; 潘伟民(1963—),男,上海人,教授,硕士生导师,硕士,研究方向:计算机应用技术,网络信息安全。
  • 基金资助:
    国家自然科学基金-新疆联合基金资助项目(U1703261); 新疆维吾尔自治区研究生创新项目(XJ2019G231)

Rumor Source Detection Algorithm in Social Networks Integrating Objective Weighting Method

  1. (School of Computer Science and Technology, Xinjiang Normal University, Urumqi 830054, China)
  • Online:2021-09-14 Published:2021-09-14

摘要: 目前许多检测方法只是对信息是否为谣言进行判断,对于谣言源的研究工作较少。针对以往研究忽略将节点权值作为一项重要参数应用于谣言源检测的问题,提出一种基于谣言中心性融入客观赋权算法模型,即BEW算法。该模型首先通过熵权算法计算网络节点权值,然后基于SIR模型进行模拟网络传播,同时考虑网节点权值嵌入特征,使用社区模块化聚类算法进行聚类,最终通过MLE算法实现源点预测的目的。在4个真实的网络数据集上进行仿真实验,实验结果表明该算法对于谣言源的识别可以达到较好的效果。

关键词: 谣言源检测, SIR模型, MLE, 谣言中心性, 权值

Abstract: At present, many detection methods only judge whether the information is a rumor, and there is less research on the source of the rumor. Aiming at the problem of ignoring the application of node weights as an important parameter in rumor source detection in previous studies, a model of objective weighting algorithm based on rumor centrality, namely BEW algorithm, is proposed. The model firstly calculates the weights of network nodes through the entropy weight algorithm, and then simulates network propagation based on the SIR model, while considering the embedded characteristics of the network node weights, and finally achieves the purpose of source point prediction through the MLE algorithm. Simulation experiments are carried out through 4 real networks. The experimental results show that the algorithm can achieve better results in identifying the source of rumors.

Key words: rumor source detection, SIR model, MLE, rumor centrality, weigh