摘要
[目的/意义]探讨政府干预和主流情绪引导对突发事件网络舆情群体负面情绪转移和演化的影响,为政府舆情治理提供理论依据。[方法/过程]基于社会影响理论,分析政府干预和主流情绪引导对群体情绪转移的影响,提出一种基于政府干预-主流情绪的突发事件网络舆情群体情绪演化模型。采用EGM(1,1)作为基础演化模型,并运用简化粒子群算法(SPSO)描述群体情绪间的转移和演化。最后结合“东方之星”沉船事故、“8·12”天津滨海爆炸事故和“长春长生疫苗”事件验证模型可行性。[结果/结论]结果表明,该模型能够刻画主流情绪对负面情绪的引导能力,以及不同情绪和不同强度下政府干预对主流情绪引导能力的影响;能够很好地描述群体负面情绪向其他情绪转移的方向和程度,以及群体负面情绪的演化趋势。
[Purpose/Significance]Discussing group negative emotion transformation and evolution of network public opinion on emergencies under the government intervention and main emotion guidance,it provides theoretical basis for public opinion governance.[Method/Process]Based on social influence theory,this paper analyzes the influence factors of government intervention and main emotion guidance on group emotions transformation and evolution,and an evolution model of group emotions is proposed.EGM(1,1)is adopted as the basic evolution model and Simplified Particle Swarm Optimization Algorithm(SPSO)is introduced to describe the transformation and evolution among group emotions.Finally,the"Eastern Star"shipwreck accident,explosion accident in Tianjin Binhai and"Changchun Changsheng Vaccine"event were carried out to testify the model validation.[Result/Conclusion]The model can express the guidance ability of main emotion on negative emotion and the influence of government intervention on the ability of main emotion guidance under different emotions and different intensities,and describe the direction and degree of the transformation about gruop negative emotion to other emotions well,as well as group negative emotion evolution tendency.
作者
冯兰萍
严雪
程铁军
Feng Lanping;Yan Xue;Cheng Tiejun(Business School,Hohai University,Changzhou 213022;School of Economics,Nanjing University of Posts and Telecommunications,Nanjing 210023;Changzhou Key Laboratory of Industrial Big Data Mining and Knowledge Management,Changzhou 213022)
出处
《情报杂志》
CSSCI
北大核心
2021年第6期143-155,共13页
Journal of Intelligence
基金
国家社会科学基金青年项目“多元舆论场共存背景下重大突发事件舆情博弈和引导策略研究”(编号:17CXW012)研究成果之一。
关键词
突发事件
政府干预
主流情绪
群体情绪演化模型
简化粒子群算法
社会影响理论
emergencies
government intervention
main emotion
the evolution model of group emotions
simplified particle swarm optimization algorithm
social influence theory