突发网络舆情事件态势感知模型及其应用实证

An Empirical Study on the Situation A wareness Model of Sudden Network Public Opinion Events and Its Application

【目的/意义】利用态势感知理论对突发网络舆情事件的演化路径进行绘制,较好地呈现出舆情演变的态势,为网络舆情事件的引导和管控提供理论支撑。【方法/过程】基于态势感知理论,对突发网络舆情事件的态势感知模型进行构建,应用社会网络分析方法、深度学习以及TF-IDF主题模型方法,从态势察觉、态势理解和态势预测三阶段入手,分析突发网络舆情事件中的突发特征词,挖掘其形成动因,以及舆情关键节点,研判舆情发展趋势。【结果/结论】研究结果表明,通过态势感知理论对突发网络舆情事件的发展及演进趋势进行分析,不仅能够挖掘出舆情发展中的突发特征词,同时也可以对不同阶段舆情发展的特征进行揭示,把握舆情事件的演化脉络。【创新/局限】研究基于态势感知理论,创新性地对网络舆情事件的突发特征词和动因进行挖掘,对舆情的演化路径进行分析和研判。未来可结合不同事件、不同评论数据,增强研究的细粒度和普适性。

[Purpose/significance]Using situational awareness theory to draw the evolutionary path of sudden network public opinion events can better present the trend of public opinion evolution,providing theoretical support for the guidance and control of network public opinion events.[Method/process]Based on the theory of situational awareness,a situational awareness model for sudden net-work public opinion events is constructed.Social network analysis methods,deep learning,and TF-IDF theme model methods are ap-plied to analyze the sudden characteristic words in sudden network public opinion events from three stages:situational awareness,situ-ational understanding,and situational prediction.The main driving forces for generating public opinion are explored,and finally,key nodes in public opinion are excavated,and the development trend of public opinion is analyzed.[Result/conclusion]The research re-sults indicate that analyzing the development and evolution trends of sudden network public opinion events through situational aware-ness theory can not only uncover the sudden characteristic words in public opinion development,but also reveal the characteristics of public opinion development at different stages,grasping the evolutionary context of public opinion events.[Innovation/limitation]Based on the theory of situational awareness,this study innovatively explores the sudden characteristic words and motivations of online public opinion events,analyzes and judges the evolution path of public opinion.In the future,different events and comments can be combined to enhance the granularity and universality of research.