Extracting and visualizing trust relationships from online auction feedback comments

Authors:
John O'Donovan;Barry Smyth;Vesile Evrim;Dennis McLeod
Affiliations:
Adaptive Information Cluster, School of Computer Science and Informatics, University College Dublin, Ireland;Adaptive Information Cluster, School of Computer Science and Informatics, University College Dublin, Ireland;Semantic Information Research Laboratory, Department of Computer Science, University of Southern California, Los Angeles;Semantic Information Research Laboratory, Department of Computer Science, University of Southern California, Los Angeles
Venue:
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Year:
2007

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Abstract

Buyers and sellers in online auctions are faced with the task of deciding who to entrust their business to based on a very limited amount of information. Current trust ratings on eBay average over 99% positive [13] and are presented as a single number on a user's profile. This paper presents a system capable of extracting valuable negative information from the wealth of feedback comments on eBay, computing personalized and feature-based trust and presenting this information graphically.