A Model of a Trust-based Recommendation System on a Social Network

Nonlinear Sciences – Adaptation and Self-Organizing Systems

Scientific paper

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v3 revised as compared to v2 (figures updated, clarifications). Accepted for publication in J. Autonomous Agents and Multi-Age

Scientific paper

10.1007/s10458-007-9021-x

In this paper, we present a model of a trust-based recommendation system on a social network. The idea of the model is that agents use their social network to reach information and their trust relationships to filter it. We investigate how the dynamics of trust among agents affect the performance of the system by comparing it to a frequency-based recommendation system. Furthermore, we identify the impact of network density, preference heterogeneity among agents, and knowledge sparseness to be crucial factors for the performance of the system. The system self-organises in a state with performance near to the optimum; the performance on the global level is an emergent property of the system, achieved without explicit coordination from the local interactions of agents.

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