WWW/Internet - Portal do Software Público Brasileiro

ISBN: 978-972-8939-25-0 © 2010 IADISis difficult for new comers to find a foothold, even if those own the same technology and service. They canonly wait for next revolutionary opportunity. It is unfair and is not good news for competing, progress oftechnology and customers. However, in the virtual network community, it is possible to improve the situation.Although there is already lots of literature on reputation research [Paul Resnick et al, 2000; Bin Yu andMunindar P. Singh, 2003; Gayatri Swamynathan et al, 2008; Ebrahim Bagheri et al, 2009], no one hasconcerned the fairness issue of online reputation systems.In this paper, we propose a novel algorithm to enhance C2C e-commerce reputation system fairness.Based on the transaction social network, our algorithm employs the random walk strategy to computemember reputation.2. C2C COMMUNITY MEMBER REPUTATION INCREMENTEVALUATION FORMULAA non-trivial C2C e-commerce community member reputation increment evaluation formula is proposed inthis section, where reputation increment means the increment of member reputation after a successfultransaction. We believe the formula for evaluating increment of member reputation after a successfultransaction should consider the following factors: the score given by one’s transaction partner, the reputationof the transaction partner, the transaction value and the encouragement-punishment factor.The score given by one’s transaction partner reflects whether the member’s behavior satisfies his or herpartner, for example, whether the commodity quality or service is as promised, whether the payment is in time.Transaction value is an important factor for evaluating member’s reputation. In general, the larger thetransaction value is, the bigger the transaction risk will exist. If a member can still keep honest in transactionsof high value, then he deserves trust relatively. If transaction value is not considered in reputation incrementevaluating formula and the increment of reputation has nothing to do with transaction value, then gamblerswill accumulate their reputation in transactions of small value and cheat in transactions of large value.Encouragement or punishment factor is used to encourage a member to keep transaction contract or punish amember for breaking transaction contract. In human society, trust increases slowly and decreases quickly.Therefore, encouragement factor should be much smaller than punishment factor.In this paper, {1, 0, -1} is taken as the score rate set. Score rate 1, -1 reflect that a member is satisfactory orunsatisfactory with his transaction partner’s behavior, respectively. Score rate 0 is neutral between 1 and -1.Since the feedback of members is usually based on intuition, we believe that it is reasonable to set only threerates. Some large electronic commerce sites also adopt {1, 0, -1} as the score rate set, like eBay.Denote by m, R(m) a member in C2C e-commerce community and m’s reputation value, respectively. Let sbe the score given by one’s transaction partner after a successful transaction and w be the transaction value.After a successful transaction, the increment of a participator’s reputation has much to do with the reputationof his or her transaction partner, the score given by the partner and the transaction value. We use the followingformula to calculate the increment of a member m’s reputation after a successful transaction.⎧ c ( R + w ) p 1 s = 1⎪∆ R ( m ) = ⎨ 0 s = 0⎪⎩ c R + w p s = −( ) 2 1Here, p 1 and p 2 are the encouragement factor and punishment factor, respectively, and R is the reputationvalue of the transaction partner, c is a small reputation constant (c