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作 者:熊励[1] 陆梦园 王锟 Xiong Li;Lu Mengyuan;Wang Kun(School of Management,Shanghai University,Shanghai 200444)
机构地区:[1]上海大学管理学院,上海200444
出 处:《智库理论与实践》2024年第2期1-12,共12页Think Tank:Theory & Practice
基 金:国家社会科学基金重大项目“基于新一代信息技术提高应对突发公共卫生事件能力研究”(项目编号:21ZDA105)的研究成果之一。
摘 要:[目的/意义]网络舆情信息在突发事件应对中有着不容忽视的传播影响力。完善舆论引导是中国特色新型智库的重要功能之一。做好网络舆情识别是应急管理智库提高综合研判能力的关键。[方法/过程]本文从应急管理智库建设角度出发,聚焦突发事件网络舆情信息中潜在的关键热点与情感结构识别问题,通过机器学习方法构建LDA-LDNB网络舆情信息挖掘模型,并基于突发事件网络舆情文本信息进行模型验证和实证分析。[结果/结论]本文构建的模型能很好地识别突发事件中网络舆情信息的主题、情感与演化特征,为应急管理智库提高应急管理决策服务能力提供方法支持,为构建数据驱动的应急管理智库提供新的思路。[Purpose/Significance]Network public opinion information has a significant communication influence in emergency response.Improving public opinion guidance is one of the important functions of new think tanks with Chinese characteristics,and effectively identifying network public opinion is the key for emergency management think tanks to enhance their comprehensive research and judgment abilities.[Method/Process]From the perspective of constructing emergency management think tanks,this paper focuses on identifying potential key hotspots and emotional structures in network public opinion information related to emergencies.It constructs the LDA-LDNB network public opinion information mining model using the machine learning method,and conducts model validation and empirical analysis based on the textual information from network public opinion regarding emergencies.[Result/Conclusion]The results demonstrate that the model constructed in this paper can effectively identify the themes,emotions and evolutionary features of network public opinion information during emergencies,provide methods and decision-making support for emergency management think tanks to improve their ability to participate in network public opinion research and judgment for emergency management decision-making services,and offer a new way of thinking for constructing a data-driven emergency management think tank.
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