eTrust: understanding trust evolution in an online world

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. Categories and Subject Descriptors H3.3 [Information Storage and Retrieval]: Information Search and Retrieval—Information filtering ...

• Type: Journal
• Year: 2012
• Where: KDD
• Authors: Jiliang Tang, Huan Liu, Huiji Gao, Atish Das Sarmas
• Keywords: Data Mining, Information Storage And Retrieval, KDD 2012, Passive Observation, Social Science Theories