Abstract
Internet auctions are used everyday by millions. However, despite frequent criticism, only the most simple reputation systems are used by the most popular Internet auctions today. As a consequence of this, an experienced auction user is forced to undergo the menial task of reading and judging comments about his potential transaction partners. While it is true that the human mind is the best possible method of evaluating this information, the task is time-consuming and error-prone: the sheer number of comments is sometimes an obstacle to making a good decision under uncertainty. An inexperienced auction user, on the other hand, is often daunted by the task of understanding the information provided to him. It takes some learning to understand the value of a negative feedback, to evaluate the contents of the comments, or to understand what it means that the auction system has returned the handling fee. The reason for this situation may be the fact that the management of auction sites uses other mechanisms, like auction insurance or escrow, to protect users against outright fraud. And, as has been argued by the management of auctions sites when we have had an opportunity to discuss the issue, the simplicity of the presently used reputation system is an added bonus: it creates the impression of a simple, easy-to-understand tool. The fact that this simple tool is vulnerable to several adversary strategies [1,2,3] and that its design has an adverse impact on the reporting behavior of users [4,5] is not a sufficient argument for a change.
The work reported in this paper has been funded by the Polish Ministry of Science and Higher Education under the research grant N N516 4307 33.
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Kaszuba, T., Turek, P., Wierzbicki, A., Nielek, R. (2010). ProtoTrust: An Environment for Improved Trust Management in Internet Auctions. In: Grundspenkis, J., Kirikova, M., Manolopoulos, Y., Novickis, L. (eds) Advances in Databases and Information Systems. ADBIS 2009. Lecture Notes in Computer Science, vol 5968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12082-4_18
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