基于深度学习的医患舆情多维演化仿真分析  

Research on Multi-Dimensional Evolution Model of Doctor-Patient Public Opinion Based onDeep Learning

作　　者：谭旭[1,2] 吴璞 蒋知义[1] 邹凯[1] 吕欣 TAN Xu;WU Pu;JIANG Zhiyi;ZOU Kai;LYU Xin(School of Public Administration,Xiangtan University,Xiangtan,Hunan 411105,China;COME Center,Shenzhen Institute of Information Technology,Shenzhen,Guangdong 518172,China;School of System Engineering,National University of Defense Technology,Changsha 410076,China)

机构地区：[1]湘潭大学公共管理学院,湖南湘潭411105 [2]深圳信息职业技术学院素质赋能中心,广东深圳518172 [3]国防科技大学系统工程学院,长沙410076

出　　处：《计算机工程与应用》2023年第19期82-91,共10页Computer Engineering and Applications

基　　金：广东省普通高校创新团队及特色创新项目(2020KCXTD040,2020KTSCX302);深圳市自然科学基金重点项目(202008291726500001)。

摘　　要：为了探析医患关系近年来的情感演化过程,助力政府部门决策干预提供理论依据,从而更好引导网络舆论走向,促进和谐医患关系的构建。针对互联网复杂语境下大规模医患舆情文本数据,在BERT预训练模型下游任务中构建情感分类器,并与LDA主题抽取技术相结合进行多维情感演化仿真分析,最后结合ARIMA模型进行情感走势预测。通过实验分析表明,LDA-BERT医患舆情多维情感分析模型的情感预测准确度达到98%,ARIMA医患舆情时间序列预测模型的预测平均误差低于11.25%,证明其能够有效运用于大规模医患舆情演化的多维度监测与分析。It can better guide the trend of network public opinion and improve the relationship between doctors and patients by analyzing the sentiment evolutionary trends of doctor-patient relationships in recent years and assisting the government in providing the theoretical basis for decision-making and intervention.In the large-scale public opinion text of doctors and patients in the complex context of the Internet,it has constructed a sentiment classifier in the downstream tasks of the pre-training model BERT.It is combined with LDA topic extraction technology for multi-dimensional emotional evolution analysis.Finally,the ARIMA model is combined to predict sentiment trends.The experimental results show that the sentiment prediction model accuracy based on LDA-BERT reaches 98%.The average prediction error of the ARIMA time series prediction of the doctor-patient public opinion model is less than 11.25%.It is demonstrated that the algorithm presented in this research can be effectively applied to the multi-dimensional monitoring and analysis of large-scale doctor-patient public opinion evolution.

关 键 词：医患舆情 LDA-BERT模型 ARIMA模型 情感演化 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]