4.8 Article

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

Journal

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2022.122177

Keywords

Blockchain technology; Network public opinion; Smart contract; Risk Association Tree; Smart ledger

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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. A smart contract is used to build a risk management system of NPO, enabling the tracing of public opinion through a smart ledger. The study introduces blockchain, NPO, and related theories, discusses the network situation of public opinion dissemination in the blockchain environment, implements a BT-based risk management model for NPO, and conducts experiments to verify its effectiveness. The research also optimizes the theoretical framework of NPO credibility model detection based on the public opinion risk prediction model. The results show that the experimental schemes could reasonably predict and detect the risk and credibility of NPO under the BT, contributing to the optimization of network environment control measures.
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 optimi-zation, 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 experi-ments 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.

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