Towards Improved Trust Diffusion Through Active Recommender Propagation
Trust is an important and frequently studied concept in personal interactions and business ventures. As such, it has been examined by multitude of scientists in diverse disciplines of study. Over the past years, proposals have been made to model trust relations computationally, either to assist users or for modeling purposes in multi-agent systems. These models rely implicitly on the social networks established by participating entities, be they autonomous agents or internet users. At the same time, research in complex networks has revealed mechanisms of information diffusion, such as the spread of rumors in a population. By adapting rumor-spreading processes and social filtering through voting to recommender nomination in multi-agent systems, this paper shows the benefit of augmenting an existing trust model with the power to actively change the topology of the social network underlying agent relationships.
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