Impact of information on public opinion reversal-An agent based model

Reversal of public opinion is an important phenomenon of opinion evolution besides consensus and polarization. Information released by someone often boosts others to change their opinion because the basis of their opinion decision is enriched. As an important external force, information may change the trend of opinion evolution, even reverse the state of public opinion. In order to explore the impact of information on public opinion evolution in macro level, especially reversal, this paper models information as a variable and embeds it into bounded confidence model based on agent based simulation, and then validates the model based on an empirical case. Information strength, time of releasing information and different types of information countermeasure are analyzed through a large number of simulation experiments to find out principles of public opinion reversal. The result shows that information released during the event can change and even reverse the orientation of public opinion, but different releasing mode will produce different result of public opinion evolution.