Polarization in a group’s opinions drives to disagreements and dissent among individuals, which make it harder to achieve group satisfactory decisions. Within Group Decision Making (GDM) problems to soften disagreements, lots of consensus reaching processes (CRPs) have been proposed to converge opinions but rarely consider the existing dynamic relationships among the experts. Meanwhile, Opinion Dynamics studies the evolution of opinions based on the relationships existing among the group members by using Social Network Analysis (SNA). In real-world GDM problems the application of CRPs alone may not be enough to achieve the desired level of agreement when there is too much dissent among experts. In this paper, a novel framework is proposed that hybridizes both the process of making closer opinions realized by CRPs and the evolving relationships among experts based on SNA. This new framework addresses when it might be impossible to achieve the agreement through CRPs, which tries to achieve a potential consensus considering that if opinions are too polarized, maybe different stable opinions states are still suitable and easier to achieve by applying a SNA together with the CRP. This framework is further analyzed through simulation experiments for demonstrating its validity and some properties.