社交网络上基于信息驱动的行为传播研究

针对社交网络上信息与行为的交互作用与协同传播的特点,建立了基于信息驱动的行为传播模型。该模型综合反映了社交网络上信息与行为传播的交互性,以及信息传播的记忆性、时效性与社会加强效果等多种因素对传播的影响。研究发现,信息的时效性、社会加强效果、信息的转播率等模型参量,以及源节点的度与核数、节点的度及与源节点距离等网络参量,都在一定程度上影响行为传播的速度和范围,但各参量在不同环境下发挥不同的作用。

Information-Driven Behavior Spread on Social Networks

In this paper, a novel behavior spreading model is proposed, which incorporates the reciprocal interaction and collaborative spreading of information and behavior on social networks. Various network parameters and transmission factors, describing the interaction of information and behavior, the memory and timeliness of information, the social reinforcement and so on, are incorporated into the spreading process. The simulation results indicate that the involved parameters have important influence on the transmission range and speed, but their functions are varied according to different circumstances. Our research shows that the behavior spreading on social networks not only possesses some common laws similar to the transmission of information and diseases, but also exhibits its unique characteristics.