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A two-fold personalized feedback mechanism is established for consensus reaching in social network group decision-making (SN-GDM). It consists of two stages 1) generating the trusted recommendation advice for individuals and 2) producing a a personalized adoption coefficient for reducing unnecessary adjustment costs. A uninorm interval-valued trust propagation operator is developed to obtain an indirect trust relationship, which is used to generate personalized recommendation advice based on the principle of ``a recommendation being more

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