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Treextrust: topic-awarecomputational trust based oninteraction experience, reputationof users with similarity, and pathalgebra of graph in social networks

Tran Dinh Que

Computer Science

2025

T. 26 (2)

The trust measure is the confidence or reliability among users or peers, whichhas been studied widely in online social networks. Most trust models are cur-rently based on the concepts of interaction trust and reputation trust; however,various forms of interactions and analyses of the interaction contexts have notbeen considered fully for trust estimation. Moreover, the mechanism for com-puting reputation trust based on propagation lacks a clear foundation and isexpensive in computation. The purpose of this paper is to present a family ofcomputational trust models (called TreeXTrust) to estimate the trust degree ofa usertrusteron another usertrustee. Our model is a mathematical formulationthat is based on an aggregation of topic-aware experience trust with variousforms of interactions and topic-aware reputation trust with users’ similarityand operators on path algebra in a graph. We conducted experiments to eval-uate the impacts of interaction forms and users’ interests on experience trustand the correlation of experience trust and reputation trust on overall trustestimation. Our experimental results demonstrated the following: (i) interestdegrees influenced experience trust more than interaction ones did; (ii) a com-munity’s evaluation of some trustee affected an overall trust estimation morethan a truster’s individual evaluation did. Our family of models outperformedthe state-of-the-art methods that have been presented in the literature and isa framework for selecting and implementing a suitable model of computationaltrust for our problem at hand.