Large-scale group decision making (LSGDM) is very common in real world, and especially how to reach a relatively consensus status in a social network is a hot topic. In this paper, we propose a concept of two-tuple linguistic trust/distrust relationship (LTR) which could present both trust and distrust degrees by semantics. The trust/distrust representation scheme can unburden individuals from providing numerical trust or distrust degree to just presenting linguistic variables. Transformation rule from two-tuple LTR to numerical trust degree is then analyzed, followed by the propagation operator of indirect trust/distrust relationships. The advantage of the propagation operator lies in that ignorance in trust/distrust relationships can be tackled rationally. As for the consensus reaching process (CRP), three-level identification and adjustment mechanisms are proposed under the condition that individuals express their preferences in an uncertain distribution form. Trust relationship, consensus degree and reliability of individuals’ judgments are all addressed comprehensively to narrow the opinion divergence. Self-confidence extent is utilized as a factor to adjust the opinions of non-consensus experts. The proposed method is further implemented in life cycle sustainability assessment to demonstrate the validity and effectiveness in dealing with realistic GDM problems.