DeciTrustNET: A graph based trust and reputation framework for social networks




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Peer reviewed



The world wide success of large scale social information systems with diverse purposes, such as e-commerce platforms, facilities sharing communities and social networks, make them a very promising paradigm for large scale information sharing and management. However the anonymity, distributed and open nature of these frameworks, that, on the one hand, foster the communication capabilities of their users, may contribute, on the other hand, to the propagation of low quality information, attacks and manipulations from users with malicious intentions. All of these risks could end up decreasing users' con dence in these systems and in a reduction of their utilisation. With these issues in mind, the objective of this contribution is to create DeciTrustNET, a trust and reputation based framework for social networks that takes into consideration the users relationships, the historic evolution of their reputations and their pro le similarity to develop a tamper resilient network that guarantees trustworthy communications and transactions. An extensive experimental analysis of the developed framework has been carried out con rming that the proposed approach supports robust trust and reputation establishment among the users, even in social network under the presence of malicious users.


The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.


Trust, Reputation, Influence, Social networks, Decision Making, Opinion dynamics


Ureña, R., Chiclana, F., Herrera-Viedma, E. (2020) DeciTrustNET: A graph based trust and reputation framework for social networks. Information Fusion, 61, pp. 101-112


Research Institute

Institute of Artificial Intelligence (IAI)