基于CEEMDAN-BP模型的突发事件网络舆情预测研究  

Predicting Online Public Opinion in Emergencies Based on CEEMDAN-BP

作　　者：程铁军 王曼 黄宝凤 冯兰萍[2] Cheng Tiejun;Wang Man;Huang Baofeng;Feng Lanping(School of Economics,Nanjing University of Posts and Telecommunications,Nanjing 210023,China;Business School,Hohai University,Changzhou 213022,China)

机构地区：[1]南京邮电大学经济学院,南京210023 [2]河海大学商学院,常州213022

出　　处：《数据分析与知识发现》2021年第11期59-67,共9页Data Analysis and Knowledge Discovery

基　　金：国家社会科学基金项目(项目编号:17CXW012)的研究成果之一。

摘　　要：【目的】研究突发事件网络舆情发展趋势的预测问题。【方法】综合考虑多重不确定因素对网络舆情演化的影响,本文基于数据分解的研究思路,利用自适应噪声完备集成经验模态分解、BP神经网络以及相空间重构理论构建基于CEEMDAN-BP的舆情预测方法,并结合多起突发事件案例进行实证研究。【结果】研究结果表明,CEEMDAN-BP模型能够较好地预测突发事件网络舆情的发展趋势,三个案例事件舆情预测的平均绝对误差分别为8.60%、17.98%、11.97%,其模型的预测性能优于CEEMDAN-SVM、EMD-BP、EMD-SVM、BP神经网络模型以及SVM模型。【局限】实验数据是以天为单位进行统计,未能全面反映出舆情演变的变化趋势。【结论】基于数据分解构建的CEEMDAN-BP模型能够有效预测突发事件网络舆情的发展趋势,可为相关部门做好突发事件网络舆情的管控和预警提供理论支持。[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.

关 键 词：突发事件 网络舆情 CEEMDAN分解 相空间重构 BP神经网络 

分 类 号：C916[经济管理] G206[社会学]