摘要
近年来多发的网络舆情事件频繁考验着政府的导控能力,利用动态贝叶斯网络对网络舆情进行预警具有重大的现实意义。在参考现有模型的基础上,细化指标体系,增加维度,结合专家意见和实际情况,构建网络舆情预警模型,并对典型网络舆情事件进行展开分析和原因诊断。将40个网络舆情案例作为训练集导入模型,对模型进行有效性验证,得到的结果与实际基本相符。
In recent years,the frequent network public opinion events test the government’s guidance and control ability.It is of great practical significance to use dynamic Bayesian network to early warn the network public opinion.On the basis of the existing models,the index system is refined,the dimensions are added,and the network public opinion early warning model is constructed combined with expert opinions and the actual situation,and the typical network public opinion events are analyzed and diagnosed.40 cases of Internet public opinion were introduced into the model as training sets,and the effectiveness of the model was verified,and the results were basically consistent with the actual situation.
作者
马晓晗
罗文华
MA Xiao-han;LUO Wen-hua(College of Public Security Information Technology and Information,Criminal Investigation Police University of China,Shenyang 110035,China)
出处
《佛山科学技术学院学报（自然科学版）》
CAS
2022年第1期62-67,共6页
Journal of Foshan University(Natural Science Edition)
基金
辽宁省社会科学规划基金重点项目(L21AFX006)。
关键词
网络舆情
动态贝叶斯网络
预警
指标体系
network public opinion
dynamic Bayesian network
early warning
index system
