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Natural language could be a common method for individuals to specific social relationships or self-evaluation (i.e., assured or unconfident). Hence, it is important to contemplate customized linguistics in collective decisions that involve linguistic variables, because the same linguistic term set may have totally different individual numerical scales. This research develops a consensus model taking into consideration the personalized individual self-confidence and trust semantics in dynamic social network group decision-making scenarios. Firstly, an optimization model driven by best additive consistency is proposed to derive the personalized self-confidence and trust semantics of individuals. Subsequently, a trust aggregation technique supporting the shortest path is outlined for weight distribution. The proposed technique not only considers the personalized individual trust linguistics but can also effectively decrease …