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A Blockchain-based trust model for crowd environments.

Nowadays, social media has become an important platform for people to share information and opinions. More and more businesses owners and individual users rely on information shared on social media and contributed by the crowd for product promotion, decision making, etc. However, it is difficult to evaluate the trustworthiness of such information effectively as the open environment allows all people with different backgrounds and expertise to contribute. Furthermore, it gives chances for malicious users or astroturfers who pursue profits by giving fake reviews or plausible answers, and those who want to build up their business’s reputation without improving quality of good or service. For solving this challenging problem, the paper considers trust as a key element and define it in the expert-based context. Then we propose a Blockchain-based trust model for information sharing in crowd environments. The proposed model uses a weighted consensus mechanism to infer the trustworthiness of shared information basing on reviews from the crowd and defines the accuracy of an agent as the ratio of his winning reviews to his total reviews. The model can reward agents effectively equivalent to his winning reviews. Experimental results show that the proposed model has higher accuracy in defining the trustworthiness of information and obtains better Collective Intelligence than existing models.