摘要
Because unexpected emergency owns the characteristics of explosive,uncertain evolution direction and group diffusion,more and more researchers concentrate on and try to control it. In addition,considering the force of network,the information of the unexpected emergency will be spread and enlarged rapidly on internet. It is a new viewpoint using the indicator system to estimate the heat degree of net-mediated public opinion on unexpected emergency,which can reveal the underlying reasons about the formation of the heat degree. Moreover,we use BP(Back Propagation) neural network method instead of traditional subjective weight assignment to calculate the weights of the indicators which can make evaluation results more accurate and objective.
Because unexpected emergency owns the characteristics of explosive, uncertain evolution direction and group diffusion, more and more researchers concentrate on and try to control it. In addition, considering the force of network, the information of the unexpected emergency will be spread and enlarged rapidly on internet. It is a new viewpoint using the indicator system to estimate the heat degree of net-mediated public opinion on unexpected emergency, which can reveal the underlying reasons about the formation of the heat degree. Moreover, we use BP (Back Propagation) neural network method instead of traditional subjective weight assignment to calculate the weights of the indicators which can make evaluation results more accurate and objective.
基金
supported by the National Natural Science Foundation of China (Grant No. 90924029)
