财经高校图书馆微信公众号信息传播效果评价研究——基于前馈 BP 神经网络模型的实证分析

Purpose/significance] Based on the feedforward back-propagation artificial neural network, thepaper puts forward the evaluation method of WeChat Official Account information dissemination in financeand economics university library, it aims to provide reference for the operation and popularization of theWeChat Official Account of financial university library. [Method/process] According to the characteristics ofthe information dissemination of the WeChat Official Account in financial university library, starting from theelements and links in the process of information dissemination, this paper constructs an evaluation index system of information dissemination effect from five dimensions: dissemination subject, dissemination content,information carrier, dissemination skill and dissemination object. By collecting the relevant data of Wechatpublic number of 30 financial and Economic University libraries, the evaluation index system is based on thefeedforward BP neural network model. [Result/conclusion] Based on the feedforward BP Neural network,the paper put forward the evaluation method of WeChat Official Account information dissemination effect infinancial university library. Then, through empirical research, it was proved that the evaluation method has agood effect on the evaluation of the propagation effect of WeChat, and according to the evaluation results, thecountermeasures and suggestions were put forward to promote the communication effect of the WeChat Official Account in finance and economics University library.