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Improving trust modeling through the limit of advisor network size and use of referrals

Authors:

Robin CohenAuthors Info & Claims

Electronic Commerce Research and Applications, Volume 12, Issue 2

Pages 112 - 123

https://doi.org/10.1016/j.elerap.2012.08.001

Published: 01 April 2013 Publication History

Abstract

This paper explores potential improvements to the trust modeling of agents in multi-agent systems when a social network of advisors is employed as part of the trust modeling, and in particular, examines means of optimizing the number of advisors that should be maintained in the social network. We propose three such improvements, two directly relating to the limit of advisor network size by either setting a maximum size for a buyer's advisor network or setting a minimum trustworthiness threshold for agents to be accepted into that advisor network, and a third which uses an advisor referral system in combination with one of the first two network-limiting techniques. We provide experimental results in defence of our approach for two distinct trust modeling systems, and show how these optimizations can improve, sometimes significantly, the accuracy of different trust models (in the context of electronic marketplaces). We believe that the proposed techniques will be very useful for trust researchers seeking to improve the accuracy of their own trust models by setting the size and composition of advisor networks.

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Cited By

Zhao NLi H(2019)How can social commerce be boosted? The impact of consumer behaviors on the information dissemination mechanism in a social commerce networkElectronic Commerce Research10.1007/s10660-018-09326-320:4(833-856)Online publication date: 21-Jan-2019
https://dl.acm.org/doi/10.1007/s10660-018-09326-3
(2017)Effect of perceived relational characteristics of online social network on e-WOM and purchase intentionInternational Journal of Web Based Communities10.1504/IJWBC.2017.08935213:4(499-529)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJWBC.2017.089352
Majd EBalakrishnan V(2017)A trust model for recommender agent systemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2036-y21:2(417-433)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1007/s00500-016-2036-y
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Published In

cover image Electronic Commerce Research and Applications

Electronic Commerce Research and Applications Volume 12, Issue 2

April, 2013

77 pages

ISSN:1567-4223

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Copyright © Elsevier B.V. © 2012.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 April 2013

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Cited By

Zhao NLi H(2019)How can social commerce be boosted? The impact of consumer behaviors on the information dissemination mechanism in a social commerce networkElectronic Commerce Research10.1007/s10660-018-09326-320:4(833-856)Online publication date: 21-Jan-2019
https://dl.acm.org/doi/10.1007/s10660-018-09326-3
(2017)Effect of perceived relational characteristics of online social network on e-WOM and purchase intentionInternational Journal of Web Based Communities10.1504/IJWBC.2017.08935213:4(499-529)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJWBC.2017.089352
Majd EBalakrishnan V(2017)A trust model for recommender agent systemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2036-y21:2(417-433)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1007/s00500-016-2036-y
Noorian ZMohkami MVassileva JFerres LRossi GAlmeida VHerder E(2014)Self-adaptive filtering using pid feedback controller in electronic commerceProceedings of the 25th ACM conference on Hypertext and social media10.1145/2631775.2631821(267-272)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1145/2631775.2631821

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