Research on the inflexion quantification model of network public opinion monitoring based on entropy weight method and TOPSIS algorithm
Conference: ICETIS 2022 - 7th International Conference on Electronic Technology and Information Science
01/21/2022 - 01/23/2022 at Harbin, China
Proceedings: ICETIS 2022
Pages: 4Language: englishTyp: PDF
Authors:
Hu, Dayong (Heilongjiang Key Laboratory of Network Security Situation Awareness Technology, Harbin, China & Heilongjiang Network Space Research Center, Harbin, China)
Meng, Qingchuan (Heilongjiang Network Space Research Center, Harbin, China & College of Computer Science and Technology, Harbin Engineering University, Harbin, China)
Zhu, Yulin; Zhang, Honghao; Dong, Yiran (Heilongjiang Network Space Research Center, Harbin, China)
Abstract:
In order to solve the quantitative problems of indicators such as the network public opinion heat, development trend and social strengthening effect of the self media platform network public opinion, which are concerned by the network public opinion supervision department. In this paper, based on the number of public opinion carriers, netizens' emotional tendency measurement, information content sensitivity measurement and other dynamic quantitative indicators, the index system of network public opinion inflection monitoring and early warning evaluation is established. Then, the entropy weight method and TOPSIS method are used to establish the network public opinion inflection quantitative model, and the calculation method of network public opinion monitoring inflection is given. The model described in this paper can effectively analyze the trend of Internet public opinion and provide decision support for the Internet public opinion supervision department.