基于SIDR模型的谣言传播与源头检测研究  

Detecting Rumor Dissemination and Sources with SIDR Model

作　　者：陈一新 陈馨悦 刘奕 王汉桢 赖拥庆 徐扬[1] Chen Yixin;Chen Xinyue;Liu Yi;Wang Hanzhen;Lai Yongqing;Xu Yang(Department of Information Management,Peking University,Beijing 100871,China)

机构地区：[1]北京大学信息管理系,北京100871

出　　处：《数据分析与知识发现》2021年第1期78-89,共12页Data Analysis and Knowledge Discovery

摘　　要：【目的】探究谣言传播的特征,识别谣言源头,减小谣言造成的危害。【方法】在传统传染病模型的基础上,加入"辟谣者"状态,以现实中谣言传播特征为参考设置节点状态转化规则,构建基于社交网络中节点交互作用的SIDR谣言传播模型,并基于该模型提出谣言源头检测算法,利用Beam Search搜索算法进行模型优化。在理论建模的基础上,选取典型的真实谣言案例进行验证与分析。【结果】SIDR模型能够较准确地刻画现实中的谣言传播事件,源头处辟谣能够抑制谣言传播;本文提出的源头检测算法在谣言传播的初期Top5节点的识别准确率达到83%。【局限】未考虑现实中社交网络的动态变化,选取实例的代表性有限。【结论】研究结果可为谣言发展趋势的预测和谣言源头的识别提供指导。[Objective] This paper explores the characteristics of rumor sources and dissemination patterns, aiming to reduce their negative effects. [Methods] First, we added"fact checkers"to the traditional infectious disease model, and set changing rules for node status based on the characteristics of rumor dissemination. Then, we constructed a SIDR model with the node interaction in social networks. Third, we proposed an algorithm based on SIDR model to detect rumor sources. Finally, we optimized the proposed model with the Beam search algorithm.[Results] We examined the new model with real-world cases and found it accurately simulated the propagation of rumors. Identifying rumor sources could constrain their spread. The accuracy of our algorithm was up to 83% at the early stage. [Limitations] This paper does not consider the dynamic changes of social networks, and more representative cases should be included. [Conclusions] The proposed model could help us identify rumor sources and predict their development.

关 键 词：SIDR模型 谣言传播 辟谣 源头检测 

分 类 号：G350[文化科学—情报学]