关键词: 新浪微博, SIR模型, BP神经网络, 参数反演, 舆情传播

Abstract: Abstract: Concern these problems that the existing researches on public opinion propagation model are seldom combined with the actual data and digging out the inherent law of public opinion propagation from the opinion big data becomes an urgent problem,a parameter inversion algorithm of the public opinion propagation model using neural network was proposed based on the practical opinion big data.A network opinion propagation model was constructed by improving the classical disease spreading SIR model.Based on this model,the parameter inversion algorithm was used to predict the network public opinion's trend of actual cases.The algorithm can accurately predict the specific heat value of public opinion compared with the Markov prediction model.The experimental results show that the proposed algorithm has certain superiority in prediction and can be used for the data fitting,the process simulation and the trend prediction of the network emergencies’ spreading.

Key words: Sina micro-blog, SIR model, Back-Propagation neural network, parameter inversion, public opinion propagation