图书情报工作 ›› 2022, Vol. 66 ›› Issue (16): 13-23.DOI: 10.13266/j.issn.0252-3116.2022.16.002

• 专题:数智驱动的重大突发事件网络舆情传播与应急管理 • 上一篇    下一篇

重大突发事件网络舆情UGC的事理图谱构建研究——以自然灾害7·20河南暴雨为例

王晰巍1,2,3, 王小天1, 李玥琪1   

  1. 1. 吉林大学商学与管理学院 长春 130012;
    2. 吉林大学大数据管理研究中心 长春 130012;
    3. 吉林大学网络空间治理研究中心 长春 130012
  • 收稿日期:2022-03-21 修回日期:2022-06-08 出版日期:2022-08-20 发布日期:2022-08-19
  • 通讯作者: 王小天,硕士研究生,通信作者,E-mail:xiaotian170812@163.com
  • 作者简介:王晰巍,吉林大学大数据管理研究中心主任,吉林大学网络空间治理研究中心主任,教授,博士生导师;李玥琪,博士研究生。
  • 基金资助:
    本文系国家社会科学基金重大项目“大数据驱动的社交网络舆情主题图谱构建及调控策略研究”(项目编号:18ZDA310)研究成果之一。

Research on the Construction of the Event Evolution Graph of UGC of Network Public Opinions For Major Emergencies——Taking the Natural Disaster 7·20 Torrential Rain in Henan as an Example

Wang Xiwei1,2,3, Wang Xiaotian1, Li Yueqi1   

  1. 1. School of Business and Management, Jilin University, Changchun 130012;
    2. Big data Management Research Center, Jilin University, Changchun 130012;
    3. Research Center for Cyberspace Governance, Jilin University, Changchun 130012
  • Received:2022-03-21 Revised:2022-06-08 Online:2022-08-20 Published:2022-08-19

摘要: [目的/意义]利用事理图谱对重大突发事件下网络舆情UGC进行分析,可以更好地呈现舆情事件之间的因果演化过程及演化路径,从而为重大突发事件舆情疏导和管控提供一定的指导。[方法/过程]构建重大突发事件网络舆情UGC事理图谱模型,给出规则模板和句法模式,提取明确因果事件对和模糊因果事件对,结合重大突发自然灾害河南暴雨救援事件下的微博舆情分析,从而实现事理图谱构建;通过K-means聚类将相似度较高的舆情事件泛化,构建抽象事理图谱。[结果/结论]研究结果表明,利用本文构建的重大突发事件网络舆情UGC事理图谱模型,可以对网络舆情的因果事件关联关系进行分析,从而揭示重大突发事件网络舆情发展过程中的关键事件。事理图谱可以帮助更好地对重大突发事件中的网络舆情演化过程进行分析,抽象事理图谱可以帮助进一步分析网络舆情UGC的演化路径。

关键词: 重大突发事件, 事理图谱, 网络舆情, 用户生成内容

Abstract: [Purpose/Significance] Using the event evolution graph to analyze the UGC of network public opinions under major emergencies, it can better present the causal evolution process and evolution path between public opinion events, thereby providing certain guidance for public opinion channeling and management and control of major emergencies. [Method/Process] This study constructed the UGC event evolution graph model of network public opinion of major emergencies, generated rule templates and syntactic patterns, and extracted event pairs with clear causality and event pairs with ambiguous causality, combined with the Weibo public opinion topic under the heavy rain rescue event in Henan, a major sudden natural disaster, to realize the construction of event evolution graph. The public opinion events with high similarity were generalized by K-means clustering algorithm, and the abstract event evolution graph was constructed. [Result/Conclusion] The study results show that using the UGC event evolution graph model of network public opinions of major emergencies constructed in this paper, the causal event correlation of network public opinions can be analyzed, so as to reveal the key events in the development process of network public opinions for major emergencies. Evolution graph model can help to better analyze the evolution process of network public opinions in major emergencies, abstract event evolution graph can help to further analyze the evolution path of network public opinion UGC.

Key words: major emergencies, event evolution graph, network public opinion, user-generated content

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