跨社交媒体的网络舆情风险预警模型研究OA

[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 pro-viding 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.