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Personalizing Trust in Online Auctions

Citation

O'Donovan, J and Evrim, V and Smyth, B and McLeod, D and Nixon, Paddy, Personalizing Trust in Online Auctions, Stairs 2006: proceedings of the third starting AI researchers' symposium, 28 Aug - 1 Sept, 2006, Riva del Garda, Italy, pp. 72-83. ISBN 1-58603-645-9 (2006) [Refereed Conference Paper]

Abstract

The amount of business taking place in online marketplaces such as eBay is growing rapidly. At the end of 2005 eBay Inc. reported annual growth rates of 42.5% [3] and in February 2006 received 3 million user feedback comments per day [1]. Now we are faced with the task of using the limited information provided on auction sites to transact with complete strangers with whom we will most likely only interact with once. People will naturally be comfortable with old fashioned "corner store" business practice [14], based on a person to person trust which is lacking in large-scale electronic marketplaces such as eBay and Amazon.com. We analyse reasons why the current feedback scores on eBay and most other online auctions are too positive. We introduce AuctionRules, a trust-mining algorithm which captures subtle indications of negativity from user comments in cases where users have rated a sale as positive but still voiced some grievance in their feedback. We explain how these new trust values can be propagated using a graph-representation of the eBay marketplace to provide personalized trust values for both parties in a potential transaction. Our experimental results show that AuctionRules beats seven benchmark algorithms by up to 21%, achieving up to 97.5% accuracy, with a false negative rate of 0% in comment classification tests compared with up to 8.5% from other algorithms tested.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Web Technologies (excl. Web Search)
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Information Processing Services (incl. Data Entry and Capture)
UTAS Author:Nixon, Paddy (Professor Paddy Nixon)
ID Code:69457
Year Published:2006
Deposited By:Research Division
Deposited On:2011-04-20
Last Modified:2012-03-21
Downloads:0

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