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Risk prediction and credibility detection of network public opinion using blockchain technology

Author

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  • Wang, Zeyu
  • Zhang, Shuting
  • Zhao, Yuanyuan
  • Chen, Chuan
  • Dong, Xiufang

Abstract

This study aims to improve the accuracy of risk prediction and credibility detection of network public opinion (NPO) and optimize the network environment. Using blockchain technology (BT) network system for optimization, a smart contract is used to build a risk management system of NPO, so that public opinion can be traced through the smart ledger using risk association tree technology. First, BT, NPO, and related theories of risk management are introduced. Second, the network situation of public opinion dissemination in the blockchain environment is discussed. Finally, a BT-based risk management model of the NPO is implemented, and experiments are conducted to verify the effect of the model. Furthermore, the theoretical framework of NPO credibility model detection is optimized according to the public opinion risk prediction model. The research results reveal that the three experimental schemes reached the peak density of the number of public opinion disseminators in the third step, and the highest values were 0.1335, 0.1318, and 0.1296, respectively. Moreover, the density of public opinion dissemination in the three experimental schemes reached a stable state of 0.087, 0.088, and 0.0898, respectively after 48 steps. Under BT, the designed three experimental schemes can reasonably conduct the risk prediction and credibility detection of NPO. This work contributes to optimizing the control measures of the network environment.

Suggested Citation

  • Wang, Zeyu & Zhang, Shuting & Zhao, Yuanyuan & Chen, Chuan & Dong, Xiufang, 2023. "Risk prediction and credibility detection of network public opinion using blockchain technology," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:tefoso:v:187:y:2023:i:c:s0040162522006989
    DOI: 10.1016/j.techfore.2022.122177
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    References listed on IDEAS

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    7. Zhang, Jingshen & Zhou, Xinzhu & Bai, Rong & Dong, Haoyang & Tang, Tingting & Wang, Zeyu & Yang, Ya & Huang, Feng, 2024. "Impact of environmental supervision reform on green innovation in mineral enterprises," Resources Policy, Elsevier, vol. 88(C).
    8. Run Tang & Xin Guan & Junfan Zhu & Bo Liu & Zeyu Wang & Fanbao Xie, 2023. "Evaluation of Sustainable City and Old-Age Security Policy Intervention in China," Sustainability, MDPI, vol. 15(7), pages 1-15, April.
    9. Xiaoyan Peng & Xin Guan & Yanzhao Zeng & Jiali Zhang, 2024. "Artificial Intelligence-Driven Multi-Energy Optimization: Promoting Green Transition of Rural Energy Planning and Sustainable Energy Economy," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
    10. Gao, Shiya & Guan, Xin & Tang, Run & Zhu, Junfan & Wang, Zeyu & Xu, Wei, 2023. "Resource curse, economic efficiency and green recovery based on three-subject framework," Resources Policy, Elsevier, vol. 85(PB).
    11. Jin, Ting & Liang, Feiyan & Dong, Xiaoqi & Cao, Xiaojuan, 2023. "Research on land resource management integrated with support vector machine —Based on the perspective of green innovation," Resources Policy, Elsevier, vol. 86(PB).

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