<p>This article investigates a new community detection algorithm under social networks and then proposes a two-stage weight determination method for subgroups to reach group consensus. To do that, it constructs a trust similarity index (TSI) by taking comprehensively into account the preference similarity, coordination cost similarity, and trust relationship among the DMs. The advantage of the TSI lies in dividing the DMs into groups with similar willingness to adjust by the coordination cost, thereby promoting group consensus. Then, a two-stage subgroup weight determining method is proposed as: the first stage considers subgroup size and cohesion, while the second stage calculates subgroup weights by integrating coordination cost with the group’s attitude towards cost. In addition, the simulation experiments confirm that this approach has the advantages of balancing subgroup characteristics. Therefore, by incorporating a consensus model, a two-stage subgroup weight based consensus model is constructed, which not only enhances group decision-making efficiency but also minimizes decision costs. Finally, the proposed model is applied to a case study on group tourism cruise decisions, validating its effectiveness and applicability and demonstrating the advantages of the proposed method.</p>