Affiliation:
1. Department of Computer and Information Science, Indiana University Purdue University Indianapolis, Indiana, USA
Abstract
We propose a trust management framework based on measurement theory to infer indirect trust in online social communities using trust’s transitivity property. Inspired by the similarities between human trust and measurement, we propose a new trust metric, composed of impression and confidence, which captures both trust level and its certainty. Furthermore, based on error propagation theory, we propose a method to compute indirect confidence according to different trust transitivity and aggregation operators. We perform experiments on two real data sets, Epinions.com and Twitter, to validate our framework. Also, we show that inferring indirect trust can connect more pairs of users.
Funder
Lilly Endowment, Inc.
National Science Foundation
Indiana METACyt Initiative
Indiana University Pervasive Technology Institute
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
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