一种真假信息传播能力评估的动态规划算法

Dynamic Programming Algorithm for True and False Information Diffusion Ability

随着互联网的快速发展,各种社交平台在帮助人们获取信息的同时,也为虚假信息的扩散提供了途径.大量虚假信息的爆发式传播不仅危害了公众的利益,而且为社会稳定带来了巨大的风险.针对社交网络中的真假信息传播模型,一种基于动态规划的计算方法在文章中被提出,该方法通过计算网络中每个节点的近似传播概率对整个网络的信息传播能力进行评估,避免了传统基于蒙特卡罗仿真方法中实验效率和结果精度难以平衡的问题.文章中的实验部分将本文提出的算法与基于蒙特卡罗的仿真方法进行了对比,结果表明该算法在对真假信息的传播能力做出有效评估的同时,大幅度提升了计算效率,为研究不同拓扑结构对真假信息的传播影响和寻找最优信息过滤能力的网络结构提供了便捷的途径.

With the rapid development of the Internet,people share information and ideas on various social platforms,which also provide w ays for the dissemination of false information.The large-scale cascading propagation of fake messages will do harm to the public and bring incalculable risks to social stability.For the information diffusion model in the social network,a dynamic programming algorithm for evaluating the true and false information diffusion abilityhas been proposed in this paper.This method estimates the filtering ability by calculating the approximate propagation probability of each node in the netw ork.It avoids the problem of the difficult balance betw een experimental efficiency and accuracy of results in the traditional Monte Carlo simulation method.We conducted comparative analyses of the two methods.The results show that the proposed method can effectively evaluate the filtering ability of the social netw ork w hile improving computing efficiency.It provides convenience to study the impact of different typologies on the spread of messages and find netw ork structure with optimal information filtering ability.