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Social Network Analysis for Trust Prediction

Abstract : From car rental to knowledge sharing, the connection between online and offline services is increasingly tightening. As a consequence, online trust management becomes crucial for the success of services run in the physical world. In this paper, we outline a framework for identifying social web users more inclined to trust others by looking at their profiles. We use user centrality measures as a proxy of trust, and we evaluate this framework on data from Konnektid, a knowledge sharing social Web platform. We introduce five metrics for measuring trust. Performance achieved an accuracy between 43% and 99%.
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Submitted on : Tuesday, November 28, 2017 - 5:09:07 PM
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Davide Ceolin, Simone Potenza. Social Network Analysis for Trust Prediction. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. pp.49-56, ⟨10.1007/978-3-319-59171-1_5⟩. ⟨hal-01651167⟩



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