首页|2022年四川3次地震舆情风险评估与监测研究

2022年四川3次地震舆情风险评估与监测研究

扫码查看
为准确评估与监测地震舆情风险,正确引导社会舆论方向,基于供需偏离理论,采用层次分析法和熵值法相结合的组合赋权法,构建地震舆情风险评估指标体系,以2022年四川芦山6.1级、马尔康5.8级和泸定6.8级3次地震后7 d内发布的相关微博及其评论为数据样本,衡量和评价其舆情风险.结果表明:震后24 h是地震舆情的风险监测关键时段,需要高度关注和密切观察.地震的震级较高或余震较多时,舆情风险指数波动性就会变大.构建的地震舆情风险评估指标体系,适用于对多个地震舆情风险的指标度量、动态监测及规律演变,可为震后政府与媒体的应急救援和舆论引导提供参考.
Risk Assessment and Survey of the Public Opinion on Three Earthquakes in Sichuan in 2022
In order to accurately monitor and assess the risk of earthquake-related public opinion and to correctly guide thesocial opinion,based on the theory of supply-and-demand deviation,this paper constructs a risk assessment index system of the earthquake-related public opinion using a combination weighting method which consists of the analytic hierarchy process and the entropy method.The study utilizes data samples from the posts and comments on Sina Weibo,the largest social software platform in China within 7 days after the Lushan Ms6.1 earthquake,the Maerkang MS5.8 earthquake,and the Luding MS6.8 earthquake which occurred in Sichuan province in 2022,to evaluate the risk of public opinion on these three earthquakes.The results show thatthe post-earthquake 24 hours is a critical period for the earthquake-related public opinion.The higher magnitude or the more aftershocks of an earth-quake,the larger the fluctuation of the public opinion risk index.The constructed risk assessment index system is suitable for the index measurement,dynamic observation,and evolution-law analysis of multiple risks of the earth-quake-related public opinion.The risk assessment index system can provide a reference for government's emergency response and for the mainstream social media's public opinion guidance after destructive earthquakes.

earthquake public opinionrisk assessmentdynamic monitoringSichuan

袁庆禄、方婉琳、孙瑞婷、胡军

展开 >

防灾科技学院经济管理学院,河北三河 065201

中国人民财产保险股份有限公司四川省分公司,四川成都 610016

地震舆情 风险评估 动态监测 四川

国家社会科学基金项目中央高校基本科研业务费研究生科技创新基金

20BJY265ZY20240347

2024

地震研究
云南省地震局

地震研究

CSTPCD北大核心
影响因子:0.884
ISSN:1000-0666
年,卷(期):2024.47(2)
  • 31