本文以淘宝网为例,对我国C2C电子商务当前信用评价体系存在的问题进行分析,从卖家信息、商品信息、卖家服务、买家评价等维度构建信用评价指标体系,并采用BP神经网络方法构建了信用评价模型,有效避免主观因素的影响,对卖家信用等级进行客观的预测,对我国C2C电子商务的诚信建设有一定的参考价值。 This paper takes Taobao as an example, analyzes the existing problems of C2C e-commerce current credit evaluation system in our country, builds the credit evaluation index system from the aspects of sellers’ information, product information, sellers service, buyer’s evaluation and so on, and constructs it by BP neural network The credit evaluation model effectively avoids the influence of subjective factors and objectively predicts the credit rating of sellers, which is of certain reference value to the honesty construction of C2C e-commerce in our country.