Trend prediction model of online public opinion in emergencies based on fluctuation analysis

Liwei Xu (), Jiangnan Qiu () and Jie Zhai ()
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Liwei Xu: Dongbei University of Finance and Economics
Jiangnan Qiu: Dalian University of Technology
Jie Zhai: Dalian University of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 116, issue 3, No 21, 3320 pages

Abstract: Abstract Prior research has ignored the influence of fluctuation factors on online public opinion in emergencies, which has led to low prediction accuracy. This paper determines fluctuation factors through text analysis and emotional calculation; it identifies the main factors that cause the fluctuation in public opinion through the Granger causality test. Furthermore, we built a trend prediction model based on the gray prediction model and optimized it by considering the fluctuation factors of online public opinion. Optimization enhances the precision of the model and makes it more suitable to forecast trends for online public opinion. Finally, by looking at a large number of online public opinion on four kinds of typical emergencies, we verified the validity of the proposed model. In short, this paper provides a novel theoretical perspective for trend prediction of online public opinion research.

Keywords: Online public opinion in emergencies; Fluctuation factors; Emotions; Granger causality test; Prediction model (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-022-05808-8

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