信息资源管理学报 ›› 2020, Vol. 10 ›› Issue (6): 28-37.doi: 10.13365/j.jirm.2020.06.028

• 新冠疫情研究:信息资源与数据管理视角 • 上一篇    下一篇

突发公共卫生事件微博舆情主题挖掘与演化分析

曹树金 岳文玉   

  1. 中山大学信息管理学院,广州,510006
  • 出版日期:2020-11-26 发布日期:2020-12-17
  • 作者简介:曹树金,教授,博士生导师,研究方向为信息组织与信息检索、用户信息行为、网络信息管理等,Email:caosj@mail.sysu.edu.cn;岳文玉,博士生,研究方向为网络信息管理,Email:yuewy3@mail2.sysu.edu.cn。

Topic Mining and Evolution Analysis of Public Opinion on Microblog of Public Health Emergencies

Cao Shujin Yue Wenyu   

  1. School of Information Management,Sun Yat-sen University, Guangzhou, 510006
  • Online:2020-11-26 Published:2020-12-17

摘要: 探索突发公共卫生事件微博舆情传播周期中各阶段的热点主题,勾勒舆情事件主题演化的时序发展趋势,为舆情决策与分析提供科学依据。以近期发生的影响巨大的一起重大突发公共卫生事件为例,结合生命周期理论、TF-IDF特征词-权值模型以及潜在狄利克雷模型方法,将时间维度融入微博文本分析,进行包括时间序列的主题挖掘工作,挖掘隐含的主题信息和舆情演化规律,并提出相应的舆情管控策略。采用的舆情演化分析方法能够揭示突发公共卫生事件微博舆情传播周期中各阶段主题的讨论内容和时序发展趋势,研究对于优化微博平台民意收集作用和辅助相关管理部门在处理类似事件时,有效引导与控制网络舆情提供了一定的理论基础支撑和科学决策支持。

关键词: 突发公共卫生事件, 网络舆情, 主题分析, 演化分析, 舆情分析, 微博文本挖掘

Abstract: This paper is to explore the hot topics in each stage of the public opinion communication cycle of public health emergency microblog, outline the time sequence development trend of the topic evolution of public opinion events, and provide scientific basis for decision-making and analysis of public sentiment.Taking a recent public health emergency as an example, combining the life cycle theory、TF-IDF model and Latent Dirichlet Allocation (LDA) method, the time dimension is incorporated into micro-blog text analysis.The topic mining work includes time series mining of the hidden topic information and the evolution rule of public opinion, and based on the evolution trend of each stage, the corresponding public opinion management and control strategy is proposed.The proposed public opinion evolution analysis method can reveal the discussion content and time sequence development trend of each stage in the public opinion communication cycle.The research provides a theoretical basis and scientific decision support for optimizing the public opinion collection function of microblog platform and assisting relevant management departments to effectively guide and control network public opinion when dealing with similar events.

Key words: Public health emergencies, Internet public opinion, Thematic analysis, Evolutionary analysis, Public opinion analysis, Microblog text mining

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