Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (11): 59-67    DOI: 10.11925/infotech.2096-3467.2021.0525
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Predicting Online Public Opinion in Emergencies Based on CEEMDAN-BP
Cheng Tiejun1,Wang Man1,Huang Baofeng1,Feng Lanping2()
1School of Economics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2Business School, Hohai University, Changzhou 213022, China
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Abstract

[Objective] This paper tries to predict the development trend of online public opinion in emergencies. [Methods] First, we identified multiple uncertain factors affecting the evolution of online public opinion. Then, we constructed a CEEMDAN-BP prediction model combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, phase-space reconstruction and Back Propagation Network. Finally, we conducted an empirical study to examine the new model with three emergencies. [Results] Our CEEMDAN-BP model could better predict the development trend of online public opinion in emergencies. The average absolute errors of prediction in three emergencies were 8.60%, 17.98% and 11.97%, respectively. Our model’s prediction accuracy and stability were better than the existing ones. [Limitations] The experimental data was based on the daily statistics, which could not fully reflect the changing public opinion. [Conclusions] The CEEMDAN-BP model can effectively predict the development trend of online public opinion in emergencies, which helps related departments to prepare for and manage the emergencies.

Received: 25 May 2021      Published: 23 August 2021
 ZTFLH: C916
Fund:National Social Science Fund of China(17CXW012)
Corresponding Authors: Feng Lanping,ORCID：0000-0003-2334-6621     E-mail: 19941415@hhu.edu.cn