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The decision making environment has been dramatically affected by rapid developments in society and the economy. Large-scale group decision making (LSGDM) based on social network has become a vital research topic in the field of decision making science. In this paper, we propose a novel framework based on social network to manage the consensus reaching process (CRP) for LSGDM faced with incomplete information. In this framework, the large-scale group is first classified into several smaller sub-groups using a sub-group detection algorithm, based on the social network. Then, we propose an estimating method based on a collaborative filtering algorithm for estimating the missing preference information of the opinion leaders in each sub-group. The two-stage dynamic influence model for handling the consensus reaching process in LSGDM begins when the LSGDM is transformed into several smaller …