Avoiding ballot stuffing in eBay-like reputation systems

  • Authors:
  • Rajat Bhattacharjee;Ashish Goel

  • Affiliations:
  • Stanford University;Stanford University

  • Venue:
  • Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
  • Year:
  • 2005

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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.