Managing public opinion in consensus-reaching processes for large-scale group decision-making problems

In a public-related decision-making event, some people whose interests are not consistent with the result of the event may post some false information on social media to guide others against the event. Without proper management, the public's opposition may lead to the failure of the events, even causing social unrest and economic losses. In order to reduce the impact of false information on the evolution of people's opinions, this paper develops two opinion dynamics models to investigate the evolution process of opinions of decision makers and other related people on social media. Then, in order to manage the public opinion formed by all related people's opinions and ensure a smooth implementation of the result of these events in real life, a public opinion management-based consensus reaching process is proposed. Meanwhile, to improve the efficiency of management measures, people are divided into two categories based on their confidence levels. Eventually, an illustrative example and simulations are provided to demonstrate the feasibility and effectiveness of the proposed model for managing public opinion.