An evaluation model of e-commerce credit information based on social big data

To overcome the problems of low accuracy and poor stability in the evaluation of Internet trading activities, an evaluation model of e-commerce credit information based on social big data is proposed. The model will be composed of four layers: basic data layer, synthetic data layer, random model layer and integrated learning layer. The logical structure of the model is divided into social communication big data preprocessing, credit evaluation submodel establishment, evaluation submodel integration, so as to enhance the ability of the credit division model. On this basis, the credit evaluation index system is established, and the e-commerce credit information is evaluated by the BP neural network method. The results of model verification show that the model has good generalisation ability and accuracy, can distinguish important variables effectively and stably, can acquire the e-commerce credit situation more scientifically, and can control the security situation of e-commerce credit information in the social big data environment.