An Empirical Study On The Credit Rating Of Online Merchants Based On User Comment Data Mining

With the rapid development of e-commerce,the demand for shopping on the Internet is driving for the rise of e-commerce platforms.The virtual nature of transactions on the web lead to risk between buyers and sellers that lack of trust,which has become a bottleneck to further development of e-commerce.The paper researches the impact factors of the net trade credit,for improving product quality,brand promotion and service improvement by theirself of ecommerce merchant to provide the reference,so as to expecting to promote the development of electric business platform.Based on the user comments as a data source,using topics mining method to determine the impact factors of the net trade credit.Based on the decision tree method and Naive Bayes algorithm,the paper analyzes the potential relationship between thirteen factors that may affect the net trade credit and the customer is whether satisfied.The research finds that the commodity credit of the primary influencing factors is the most significant factor,and the product quality of the secondary influential factors is the decisive factors and the second influencing factors that the after sales service,delivery speed,electric business platform brand credit,distribution of accuracy,the delivery in time,commodity brand credit,online customer service,goods and packaging in good condition,commodity prices,commodity appearance,and the other two factors are less influential.Provide a reference for the user reviews data mining and the research of the electronic commerce credit.