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Trust Value Evolutionary Simulation Based a Whole-process and Multi-round Opinion Propagative Model

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Abstract

As the trust in opinion propagation is very few studied in literatures, based on a complex trust network, a whole-process and multi-round opinion propagative model including four stages from public opinion reporting to trust reward and penalty feedback is presented to study the change trends of trust values. With several source nodes holding different public opinion attitude values and propagating them in an actual complex network Kaitiaki, when a node receives contradictory attitude values, its attitude value is calculated according to a model of public opinion attitude collision. After the correct public opinion attitude value is published, all nodes are rewarded or punished depending on whether get the same direction of public opinion attitude. Based the model, the trends of trust values are obtained, and the trust values are analyzed. The results show that the trend of trust values is affected by the difference of reward and penalty values. The greater the difference is, the more obvious the positive trend of trust value is. The smaller the difference is, the more obvious the negative trend of trust value is. When the difference is zero, the trend of trust is not obviously affected.

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Acknowledgements

The authors acknowledge the Humanity and Social Science Foundation of Ministry of Education of China (No: 14YJA630079), International Exchange Program of Education Department of Hubei Province and Teachers Training Abroad Project of Hubei University of Automotive Technology in 2015.

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Correspondence to Xiangling Kuang.

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Kuang, X., Huang, G., Yang, L. et al. Trust Value Evolutionary Simulation Based a Whole-process and Multi-round Opinion Propagative Model. Wireless Pers Commun 103, 677–697 (2018). https://doi.org/10.1007/s11277-018-5470-6

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  • DOI: https://doi.org/10.1007/s11277-018-5470-6

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