Abstract: [Purpose/significance] Based on the feedforward back-propagation artificial neural network, the paper puts forward the evaluation method of WeChat Official Account information dissemination in finance and economics university library, it aims to provide reference for the operation and popularization of the WeChat Official Account of financial university library. [Method/process] According to the characteristics of the information dissemination of the WeChat Official Account in financial university library, starting from the elements 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 Wechat public number of 30 financial and Economic University libraries, the evaluation index system is based on the feedforward 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 in financial university library. Then, through empirical research, it was proved that the evaluation method has a good effect on the evaluation of the propagation effect of WeChat, and according to the evaluation results, the countermeasures and suggestions were put forward to promote the communication effect of the WeChat Official Account in finance and economics University library.
Keywords: finance and economics university library; WeChat Official Account; propagation effect; feedforward back-propagation artificial neural network; utility evaluation