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Measurement Theory-Based Trust Management Framework for Online Social Communities

Published: 24 March 2017 Publication History

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.

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Published In

cover image ACM Transactions on Internet Technology
ACM Transactions on Internet Technology  Volume 17, Issue 2
Special Issue on Advances in Social Computing and Regular Papers
May 2017
249 pages
ISSN:1533-5399
EISSN:1557-6051
DOI:10.1145/3068849
  • Editor:
  • Munindar P. Singh
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 March 2017
Accepted: 01 November 2016
Revised: 01 November 2016
Received: 01 February 2016
Published in TOIT Volume 17, Issue 2

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Author Tags

  1. Measurement theory
  2. online social communities
  3. trust inference operators
  4. trust management

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