A Reputation Revision Mechanism to Mitigate the Negative Effects of Misreported Ratings

Reputation systems aggregate the ratings provided by buyers to gauge the reliability of sellers in e-marketplaces. The evaluation accuracy of seller reputation significantly impacts the sellers’ future utility. The existence of unfair ratings is well-recognized to negatively affect the accuracy of reputation evaluation. Most of the existing approaches dealing with unfair ratings focus on filtering/discounting/aligning the possible unfair ratings caused by malicious attacks or subjective difference. However, these approaches are not effective against unfair ratings in the form of misreporting (e.g., a well-behaving buyer misjudged a seller and provided a negative rating to a transaction which deserves a positive one, and the buyer is willing to revert the misreported negative rating). In this case, how should the buyer undo the damage caused by such misreported ratings and help the seller recover utility loss? In this paper, we propose a reputation revision mechanism to mitigate...

• Type: Journal
• Year: 2015
• Where: ACMICEC
• Authors: Siyuan Liu, Chunyan Miao, Yuan Liu, Hui Fang 0002, Han Yu, Jie Zhang 0002, Yueting Chai, Cyril Leung
• Keywords: ACMICEC 2015, ECommerce