eTrust
Published 12 August 2012
Jiliang Tang, Huiji Gao, Huan Liu, Atish Das Sarma
Citations215
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TL;DR
This paper proposes a framework of evolution trust, eTrust, which exploits the dynamics of user preferences in the context of online product review and performs experiments to show how the exploitation of trust evolution can help improve the performance of online applications such as rating and trust prediction.
Abstract
Most existing research about online trust assumes static trust relations between users. As we are informed by social sciences, trust evolves as humans interact. Little work exists studying trust evolution in an online world. Researching online trust evolution faces unique challenges because more often than not, available data is from passive observation. In this paper, we leverage social science theories to develop a methodology that enables the study of online trust evolution. In particular, we propose a framework of evolution trust, eTrust, which exploits the dynamics of user preferences in the context of online product review. We present technical details about modeling trust evolution, and perform experiments to show how the exploitation of trust evolution can help improve the performance of online applications such as rating and trust prediction.
Keywords
Social SciencesComputer Science
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