Abstract
We propose a kinetic exchange opinion model with dynamic individual influence. Agents update opinions considering their current and neighbors' opinions in terms of self-confidence and heterogeneous neighboring influence. Agents' influence is initialized according to their centrality status in the network, and evolves with their opinions during the interaction. Simulation results show that heterogeneous individual influence accelerates the relaxation process. The order parameter increases with agents' confidence, but median confidence may cause more fluctuations and make individual opinions have large variance. Large change rate of influence promotes the occurrence of extremists, but may prevent the growth of large macroscopic opinion clusters. This model is helpful for understanding some collective phenomena on online social media.
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