基于无标度网络的恐怖信息传播与最优应对策略

通过BA无标度网络模型刻画社会结构,基于NetLogo软件建立异质性多主体模型,考虑随机和择优两种策略,模拟恐怖信息在网络中的传播和政府的干预措施,以研究恐怖信息传播的影响因素和政府的最优应对策略.研究结果表明:网络恐怖信息的传播速度主要取决于网络结构和个体的从众程度,与恐怖集团的传播策略关系不大.政府有效应对恐怖信息传播的最优策略取决于个体的从众程度、政府的干预范围等多方面因素:个体从众程度的增加能够有效降低政府干预措施的生效时间;政府干预范围的增大在随机应对策略和择优应对策略下均能够实现更好的干预效果.

Cyber terrorism spreading and optimal intervention policies based on a scale-free network

This paper builds a heterogenous multi-agent model based on the NetLogo software by using a BA scale-free network model to capture the social structure. Considering both random strategy and preference strategy, the spreading of terrorism in the network and intervention policy of government are simulated to study the influencing factors for the spreading and the optimal intervention strategy. The results indicate that the effects of spreading of terrorism news depend on both network structure and individuals' conformity, but have little relationship with the spreading strategy of terrorism news. The optimal intervention policy mainly depends on individuals' conformity and intervention scope, namely that a stronger conformity increases the controlling efficiency of the intervention policy. Furthermore, a larger intervention scope promotes a better result for both random intervention strategy and preference intervention strategy.