A framework to consensus opinion model within a networked social group is put forward. The current research in opinion formation within the groups is largely based on the opinion aggregation of each user of the network. However, the consistency of users in aggregation, social power and the impact of each individual user of the group for opinion formation are not considered. In this article, we investigate a consensus opinion model in social groups based on the impact of influential users and aggregation methods. In order to reach the consensus model, we aggregate the users' opinions. To maintain the consistency we propagate the opinion through the users to reach an agreement. This propagation will consider the influential users' impacts who have a crucial effect on its process. A novel method is proposed to detect the influential users and opinion propagation based on them to derive the opinion toward the networked social group. In particular, we applied Optimism and Pessimism scores as the users' personality to discover the influential users in the network. Considering that, we propagate the opinion based on two facts: (i) the impact of influential users, derived by the presence of an extremely confident individual in the network, and (ii) the impact of neighbors, induced by the presence of the users who have a connection with the current user. Then, we proposed the opinion aggregation of the group induced by the weighted averaging operator and fuzzy techniques. In order to evaluate the validity of the method, two data-sets of Epinions and Etsy are employed which are signed and unsigned, respectively. The results show that identifying the expertise of neighbors (influential users) have a crucial impact on opinion propagation and the proposed model can effectively improve the computation of consensus opinion in social shopping sites.