Trust Evolution: Modeling and Its Applications


Trust plays an important role in helping on-line users collect reliable data and it has gained increasing attention from the pc science community in recent years. Traditionally, analysis regarding online trust assumes static trust relations between users. But, trust, as a social concept, evolves as people interact. Most existing studies concerning trust evolution are from sociologists in the physical world while little work exists in an online world. Studying online trust evolution faces unique challenges because additional typically than not, offered knowledge is from passive observation. During this work, we leverage social science theories to develop a methodology that permits the study of on-line trust evolution. In specific, we have a tendency to identify the differences of trust evolution study in physical and on-line worlds and propose a framework, eTrust, to study trust evolution using online data from passive observation in the context of product review sites by exploiting the dynamics of user preferences. We tend to present technical details concerning modeling trust evolution, and perform experiments to point out how the exploitation of trust evolution can help improve the performance of on-line applications like trust prediction, rating prediction and ranking evolution.

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