Building a Credit Evaluation Model for C2C E-commerce Websites Under the Guidance of Decision Trees

Recently, C2C online shopping has gained popularity among consumers. However, with technological advancements, the virtualization, anonymization, and shortening of transaction time in online trading have led to an increase in counterfeit products, transaction disputes, and fraudulent activities. These challenges threaten the sustainable development of C2C e-commerce and have gradually become the main obstacle to its growth. This study uses a decision tree-based approach to explore the trust mechanism in e-commerce transactions under the C2C model. Additionally, visualization simulations using software like Swarm evaluate the algorithm’s effectiveness. The experiment demonstrates that this method can quickly reach a consensus and accurately detect potential risks, which will greatly contribute to establishing future credit systems.