With the growing scale of online transactions, credit become more and more important, but the credit evaluation models of current c2c platforms are too simple and can not provide a compound credit evaluation to buyers. So it's not convenient for buyers to compare the target sellers. This paper analyzes the c2c platform in China and proposes an improved model. The improved model considers the total numbers of exchanging, taking the average exchange credit score as the index which assess the seller's exchanging credit. Besides, the improved model uses entropy theory to propose a compound credit index to assess the seller's comprehensive credit. In order to determine each coefficient in the model, large scale of real c2c market data is required, so this study develops an data collection program to crawl data from current c2c platform, taobao is the target because of its market share in China. Finally this study uses another part of data to analyze the result of computation.
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