Abstract
We present a preliminary study on the robustness of binary feedback reputation systems (e.g. eBay) to ballot stuffing and bad mouthing. In a feedback based reputation system, a seller can collude with other buyers to undertake fake transactions in order to enhance her reputation. This problem is referred to as ballot stuffing. A seller can also be targeted by a group of buyers to deliberately lower her reputation. This problem is referred to as bad mouthing. For the reputations to be meaningful, any practical reputation system needs to be resistant to these problems. We use a simplified model to give an explicit relation between the reputation premium and the transaction cost that needs to hold in order to avoid ballot stuffing. Thus we draw attention to the necessity of transaction costs for a well functioning reputation system. Our conclusions are confirmed by empirical experiments on eBay. © 2005 ACM.
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CITATION STYLE
Bhattacharjee, R., & Goel, A. (2005). Avoiding ballot stuffing in eBay-like reputation systems. In Proceedings of ACM SIGCOMM 2005 3rd Workshop on the Economics of Peer-to-Peer Systems, P2PECON 2005 (pp. 133–137). Association for Computing Machinery. https://doi.org/10.1145/1080192.1080203
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