基于凝聚子群的口碑传播机制研究

采集微博营销公众号数据抽取凝聚子群构建网络，建立嵌入凝聚子群因素的信息传播模型SIRC，并以该模型为基础采用Matlab仿真口碑信息在凝聚子群网络上的传播过程，研究了口碑信息在复杂网络和子群网络的传播效应的不同，探索初始传播概率的变化对传播范围的影响，子群凝聚力的大小对传播增进概率的贡献，最后证明SIRC传播模型优于传统的传播模型。实验结果表明子群凝聚力越大，信息传播速度增快的效应越明显；初始传播概率对于信息传播速度作用一般。研究成果对于控制口碑信息传播、营销方案的制定有一定的参考。

Research of word-of-mouth communication mechanism based on cohesive subgroup

To extract subgroup from Micro-blog network and establish information dissemination model SIRC with condensed subgroup factors embedded, this paper uses Matlab to simulate information diffusion on network based on SIRC model. It studies on the different reputation information dissemination in the effect of complex networks and subgroup network. Then it investigates the influence of the change of initial propagation probability on the range of propagation and the contribution of subgroup cohesion to the probability of propagation enhancement. Finally, it proves that the SIRC propagation model is superior to the traditional ones. The results indicate that the greater the cohesive force of subgroup is, the faster the speed of information propagation will be. The initial propagation probability has a general effect on the speed of information propagation. The research results have some reference for the control of word-of-mouth, information dissemination and marketing program formulation.