Abstract
Today, the public opinion synchronization on the network platform is becoming one of important issues worthy of careful study. In this paper, we take synchronization evolution phenomenon as an objective and adopt artificial bee colony (ABC) to evaluate network synchronization effects with optimization theory to find out an appropriate network structure. Firstly, we use the Kuramoto oscillators as a metaphor of the social system collective behavior. Secondly, combined with the social network characteristics obtained from the data of Sina Micro-Blog, a synchronization evolution model of Internet public opinion based on Kuramoto one is established. Subsequently, evolutionary multi-objective optimization model is set up and the ABC method is used to optimize the level of network synchronization, the synchronization starting time and the cost of public opinion synchronization. Finally, case analysis on “Double Eleven” Internet Marketing as well as Cadmium Poisoned Rice Event demonstrates that the synchronization performance of weak coupled system can be enhanced by offering reasonable configuration of the connection cost and the synchronization duration cost. In addition, a certain degree of increase in input cost can promote the synchronization performance and extend the synchronization duration significantly.
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Acknowledgements
This research is supported by National Natural Science Foundation of China (No. 71401156 and 61540032), Zhejiang Provincial Natural Science Foundation of China (No. LY18G010001) as well as Contemporary Business and Trade Research Center and Center for Collaborative Innovation Studies of Modern Business of Zhejiang Gongshang University of China (Grant No. 14SMXY05YB).
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Xiao, R., Li, J. & Chen, T. Modeling and intelligent optimization of social collective behavior with online public opinion synchronization. Int. J. Mach. Learn. & Cyber. 10, 1979–1996 (2019). https://doi.org/10.1007/s13042-018-0854-1
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DOI: https://doi.org/10.1007/s13042-018-0854-1