基于BP神经网络的高校声誉危机预警研究

随着新媒体形式的繁荣,高校所处的社会环境日益复杂,这一变化为高校发展带来机遇的同时,也使得一些不确定因素迅速增加,高校越来越频繁地面临各种声誉危机。要降低危机危害,在"平时"做好声誉危机管理的规划工作显得尤为重要,尤其是着重关注危机发生前的预警体系构建,做到花少量的钱预防,而不是花大量的钱治疗。在总结已有相关文献基础上,文章采用BP神经网络方法,利用数据挖掘等新技术手段,研究在新媒体环境下高校声誉危机预警机制,同时以工信部属高校为例,分析目前高校危机预警机制的构建现状,以期提出相应的改进建议。

Based on the BP Neural Network of Reputation Crisis Early Warning Research

With the deepening of social change and the rapid development of information and communication industries, the social environment is becoming more and more complex, which not only brings some opportunities but also some uncertain factors at the same time. And these uncertain factors can lead to the crisis, and disrupt the university reputation. To reduce the harm the crisis brings, we should focus on the construction of crisis warning system, so that we can spend a small amount of money to prevent, rather than spend a lot of money to treat. Based on the existing literature, this paper tries to utilize the data mining techniques to study how to prevent the university crises on the new media environment by the use of BP neural network method, and thus explore the establishment of universities crisis warning system.