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Title:
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ENHANCING FAIRNESS: A NOVEL C2C E-COMMERCE COMMUNITY MEMBER REPUTATION ALGORITHM BASED ON TRANSACTION SOCIAL NETWORKS |
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Author(s):
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Wangsen Feng, Bei Zhang, Yunni Xia, Jiajing Li, Tao Meng |
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ISBN:
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978-972-8939-25-0 |
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Editors:
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Bebo White, Pedro Isaías and Diana Andone |
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Year:
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2010 |
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Edition:
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Single |
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Keywords:
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C2C e-commerce community; reputation; fairness; social network |
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Type:
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Short Paper |
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First Page:
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277 |
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Last Page:
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281 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Today, almost all the C2C e-commerce community member reputation evaluating algorithms are time sensitive. The reputation of a community member is accumulated after transactions and the increment of reputation after a successful transaction is computed based on the score given by his or her transaction partner. Since people always tend to do business with those with high reputation value, the reputation of members joined in C2C community at different time will vary greatly although they may provide the same commodity quality and service. It is unfair to new comers. In this paper, we propose a novel algorithm to overcome the shortcoming. Based on the transaction social network, our algorithm employs the random walk strategy to compute member reputation and enhance system fairness. |
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