Abstract：Because Hegselmann Krause model could’t well interpret the process of trust and interacts between individuals ,which is from quantitative change to qualitative change in a social network, a new model about group opinion evolution is established based on continuous impact function. The simulation of this model clearly shows the less clusters numbers and the shorter convergence time of group opinions with the larger the parameter of bounded confidence. If the parameter of whole impact interval is larger, the opinion clusters decreases, and the convergence time of group opinion becomes longer. But if all the individuals’ opinion is the same finally, the convergence time will be shorter with the larger of this parameter. In addition, the simulation further shows if the force of selfconfidence of individual is strong, the number of opinion clusters is always be large. If the consensus is reached finally, the convergence time of group opinions becomes longer with the stronger selfconfidence of individuals.
陆安,刘业政. 基于连续影响函数的群体观点演化模型与仿真[J]. J4, 2014, 11(2): 283-.
LU An,LIU Yezheng. Simulation of Group Opinions Evolution Model Based on Continuous Impact Function. J4, 2014, 11(2): 283-.
2014, Vol. 11 
