Research on the Early Warning Model of Online Public Opinion Risk Based on Cross-Social-Media Platforms

Authors

• Tiejun CHENG, School of Economics, Nanjing University of Posts and Telecommunications, Nanjing 210023
• Tong WANG, School of Economics, Nanjing University of Posts and Telecommunications, Nanjing 210023
• Jianxiang WEI, Library, Nanjing University of Posts and Telecommunications, Nanjing 210023
• Lanping FENG, School of Economics and Finance, Hohai University, Changzhou 213000

Keywords

cross-social-media, online public opinion, dynamic early warning, early warning threshold, early warning model

Abstract

[Purpose/significance] Under the influence of cross-social media interactions, online public opinion can ferment simultaneously across different media platforms, deeply interact, and resonate multiple times, which is more likely to trigger a chain reaction of risks or even new types of risks. Therefore, it is significant to analyze the interactive influence of risks based on cross-social media public opinion data to promote the management of online public opinion towards preemptive prevention and early warning. [Method/process] Firstly, based on the analysis of the risk characteristics of cross-social media public opinion, a risk early warning indicator system for cross-social media online public opinion is constructed, and the Analytic Hierarchy Process (AHP) is adopted to determine the indicator weights. Secondly, the optimal segmentation method is used to identify the risk early warning thresholds for Weibo and Bilibili, as well as for aggregated cross-platform online public opinion. Finally, a dynamic early warning model for cross-social media public opinion risk based on evidence theory is developed. [Result/conclusion] Through case studys on three typical events including the Henan Rainstorm Incident, the results show that the proposed model is effective and practical in dividing online public opinion warning thresholds and providing dynamic real-time risk warnings for cross-social media public opinion. The findings can provide theoretical references for the early warning and management of online public opinion on cross-social media platforms.

First Page

56

Last Page

67

Submission Date

4-Dec-2025

Revision Date

13-Mar-2026

Acceptance Date

7-Apr-2026

Published Date

1-Oct-2026

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Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2026.04.006

Recommended Citation

CHENG, Tiejun; WANG, Tong; WEI, Jianxiang; and FENG, Lanping (2026) "Research on the Early Warning Model of Online Public Opinion Risk Based on Cross-Social-Media Platforms," Journal of Scientific Information Research: Vol. 8: Iss. 4, Article 6.
DOI: 10.19809/j.cnki.kjqbyj.2026.04.006
Available at: https://eng.kjqbyj.com/journal/vol8/iss4/6