Opinions and behaviors-based public opinion management considering information dissemination for public-related large-scale group decision-making

In public-related large-scale group decision-making (PL-LGDM) events, the public disclosure of phased decision-making results affects the trajectory of public opinion, while the evolution of public opinion in turn shapes the direction of decisions that need to keep public interest in mind. Inconsistencies between public opinion and decisions can hinder or even overturn the implementation of decision outcomes, affecting social stability. Considering this interaction, this paper proposes an opinions and behaviors-based public opinion management (OB-POM) model. The model takes the fluidity of information within social networks into account and proposes the public opinion dissemination process, shifting the focus of public opinion evolution research from static to dynamic populations. A set of negative public opinion trigger conditions, encompassing both quantitative and qualitative criteria, is proposed considering public opinion and phased decision-making results. Opinion leaders are classified into four categories based on their opinions and behaviors, and targeted public opinion management strategies are proposed accordingly. Simulation results demonstrate the feasibility of the model and its effectiveness in eliminating negative public opinion and facilitating consensus among decision-makers.