Research on Mining and Application of Group Events Based on Network Public Opinion Big Data

Authors

  • Weimin Gao School of Computer Science and Engineering, Central South University, ChangSha, China 410083 and Department of Computer Science and Engineering, Hunan Institute of Technology, HengYang, China 421002 https://orcid.org/0000-0003-0912-9014
  • Jiaming Zhong College of Economic and Management, Xiangnan University, Chenzhou, China 423000 https://orcid.org/0000-0002-3428-8466
  • Yuan Xiao College of Economic and Management, Xiangnan University, Chenzhou, China 423000 https://orcid.org/0000-0003-3561-4398

DOI:

https://doi.org/10.13052/jwe1540-9589.2069

Keywords:

Mining and application; Network group events; Simulation; SIR(Susceptible Infected Recovered Model).

Abstract

Network Public Opinion is significant in maintaining social harmony and stability and promoting transparency in government affairs. However, with the development of economy and transformation of society, our country has entered a high-risk period, which is full of unexpected public events. Unexpected mass accidents also cause hot discussions among the Internet users once they are exposed on the network. Different ideas, opinions, emotions, and attitudes about unexpected public events will be collected and collide on the Internet. It makes Network Public Opinion play an increasingly important role in the evolution of unexpected public events. It could promote the spread and upgrade of unexpected public events and bring more and more profound influence on to our social life. We use the case study method to analyze and solve the problems by applying the dynamic principles of the SIR epidemic model, comprehensively considering the social environment and various influencing factors, and constructing a mathematical model for the spread of network group events. The study uses Matlab to simulate the change trajectory of the number of participants in the network group events. By adjusting the number of contacts φ in the model, the development of network group emergencies can be effectively controlled and managed. As long as the government takes timely intervention measures, the dissemination of network group events can be basically controlled. Combined with public opinion big data to discover the important factors affecting the spread of public opinion, the control effect is obvious.

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Author Biographies

Weimin Gao , School of Computer Science and Engineering, Central South University, ChangSha, China 410083 and Department of Computer Science and Engineering, Hunan Institute of Technology, HengYang, China 421002

Weimin Gao received the B.E. degrees from Nanhua University, China, in 1999 and the master’s degrees from the School of Information Science and Engineering, Hunan University, China,in 2007. He is currently pursuing the Ph.D. degree with the School of Computer Science and Engineering, Central South University, China. His current research interest is data center network.

Jiaming Zhong, College of Economic and Management, Xiangnan University, Chenzhou, China 423000

Jiaming Zhong received the B.S. degree from Hunan Normal University. Now he is a professor at Xiangnan University. His research interest is intelligent information processing. He has published more than 40 papers.

Yuan Xiao , College of Economic and Management, Xiangnan University, Chenzhou, China 423000

Yuan Xiao received the M.S. degree from Chongqing University of Technology in 2010. Now she is a lecturer at Xiangnan University. Her research interests include Financial Big Data and Intelligent Financial. She has published more than 10 papers.

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Published

2021-10-18

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