eTrust: Understanding trust evolution in an online world

Jiliang Tang, Huiji Gao, Huan Liu, Atish Das Sarmas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

104 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages253-261
Number of pages9
DOIs
Publication statusPublished - 2012
Event18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 - Beijing, China
Duration: Aug 12 2012Aug 16 2012

Other

Other18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012
CountryChina
CityBeijing
Period8/12/128/16/12

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Keywords

  • multi-faceted trust
  • trust evolution
  • user preference

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Tang, J., Gao, H., Liu, H., & Das Sarmas, A. (2012). eTrust: Understanding trust evolution in an online world. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 253-261) https://doi.org/10.1145/2339530.2339574