G-GERT network model of online public opinion reversal based on kernel and grey degree
Grey Systems: Theory and Application
ISSN: 2043-9377
Article publication date: 3 March 2021
Issue publication date: 3 January 2022
Abstract
Purpose
In recent years, online public opinion reversal incidents have been occurring frequently, which has increased the complexity of the evolution of online public opinion, and they have become a difficult issue for public opinion management and control. It is of great significance to explore the regularity of online public opinion reversal.
Design/methodology/approach
Combined with the grey characteristics of online public opinion information, a grey graphical evaluation review technique (G-GERT) network model is constructed based on kernel and grey degree, and the frequency, probability and time of online public opinion reversal nodes are calculated using C-marking method and Z-marking method.
Findings
Throughout the online public opinion reversal events, there are all repeated outbreak nodes occurring, so the authors regard the repeated occurrence of outbreak nodes as reversal. According to the average frequency, probability and time of repeated outbreak nodes in the G-GERT network model, the authors predict the corresponding key information of reversal. It can simulate the evolution process of public opinion events accurately.
Originality/value
The G-GERT network model based on kernel and grey degree reveals the regulation of public opinion reversal, predicts the frequency, probability and time of reversal nodes, which are the most concerned and difficult issues for decision-makers. The model provides the decision basis and reference for government decision-making departments.
Keywords
Acknowledgements
This work is funded by the National Natural Science Foundation of China (71801085, 71801060, 71701105, 41801119), Jiangsu postdoctoral research funding plan (1701100C), scientific research foundation of Nanjing University of Information Science and Technology, Social Science Foundation of China (18FGL003), the Key Project of National Language Commission (ZDI135-67), China Postdoctoral Science Foundation funded project (Grant No. 2018M631220), Excellent Youth Foundation of Xinjiang Scientific Committee (Grant No. 2017Q071) and Ministry of Education Foundation of Humanities and Social Sciences (No. 19YJA630039).
Citation
Yan, S., Zeng, X., Xiong, P. and Zhang, N. (2022), "G-GERT network model of online public opinion reversal based on kernel and grey degree", Grey Systems: Theory and Application, Vol. 12 No. 1, pp. 142-155. https://doi.org/10.1108/GS-09-2020-0118
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited