A visual interaction consensus approach for fuzzy social network with trust propagation

With the rapid development of the Internet and the increase in online communication, complex social relationship produces new challenges to group decision making. To deal with the group consensus problems consisting of fuzzy preference information and incomplete trust relationship, considering trust propagation, we exploit the theory and methods of network analysis, clustering, Pythagorean fuzzy set, and group decision making to construct a fuzzy information social network group consensus approach, and discuss four different scenarios of consensus (high-high, high-low, low-high and low-low) between the interest subgroups and whole social network by setting different compromise parameter values for different situations to reduce the supervision cost and keep initial opinions as much as possible. Finally, we use a vaccine selection case to verify the rationality and applicability of the proposed model.