@inproceedings{63add55483e14f128acde344a54783af,
title = "eTrust: Understanding trust evolution in an online world",
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 = "multi-faceted trust, trust evolution, user preference",
author = "Jiliang Tang and Huiji Gao and Huan Liu and {Das Sarmas}, Atish",
year = "2012",
doi = "10.1145/2339530.2339574",
language = "English (US)",
isbn = "9781450314626",
series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
pages = "253--261",
booktitle = "KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
note = "18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 ; Conference date: 12-08-2012 Through 16-08-2012",
}