[目的/意义]针对当前我国多媒体网络舆情响应问题,梳理并提出以危机风险分型为基础的政府组织响应路径整合匹配、响应工作流程模型构建机理,以期为管理决策者提升资源整合能力、网络舆情危机精准响应效力提供参考。[方法/过程]对大数据环境下网络舆情危机动力要素的作用进行分析,提取出网络舆情危机风险分型的基础系数,并以多元结构网络舆情信息的多媒体传播路径为视角提取网络舆情危机风险分型叠加系数,再逐一提取各风险分型下网络舆情危机响应的工作要点。[结果/结论]根据主体结构要素、媒体效力要素、客体属性要素危机作用形态的排序组合,在其关系节点上建立多媒体网络舆情危机等级基数。根据本体成分分化后对舆情危机的不同影响效果,建立多媒体网络舆情危机加成系数。建立多媒体网络舆情危机风险分型模型,将舆情危机风险解构为等级系数和加成系数。从而更为准确地描述舆情危机的表征,有利于判断舆情危机的未来发展态势,提高与既往舆情危机案例匹配的速度与精准度。
[Purpose/significance] Aiming at the current public opinion response problem of multimedia network in China, this paper combs and proposes the mechanism of government organization response path integration matching and response workflow model based on crisis risk classification. In order to improve the resource integration ability for management decision-makers, the network public opinion crisis provides a reference for the accurate response effectiveness.[Method/process] This paper analyzes the role of the dynamic factors of network public opinion crisis in big data environment, extracts the basic coefficients of network public opinion crisis risk classification, and extracts the network public opinion crisis risk classification superposition coefficient from the perspective of the multi-structure of network public opinion information carried by multimedia technology. Then the paper analyzes the work points of the network public opinion crisis response under each risk classification one by one.[Result/conclusion] According to the ordering combination of the main structural elements, the media effectiveness factors and the object attribute elements, the credit base level of the multimedia network is established on the relationship nodes. According to the different influence effects of the ontology component on the public opinion crisis, the public opinion crisis of the big data multimedia network is established. Establishing a multimedia network public opinion crisis risk classification model, deconstructing the public opinion crisis risk into a ranking coefficient and an addition coefficient, and a more accurate description of the lyric crisis is conducive to judging the future development of the grievance crisis and improving the speed and accuracy of matching with the previous grievance crisis case.
[1] CHI E. The Chinese government's responses to use of Internet[J].Asian perspective,2012,36(3):387-409.
[2] 谢耘耕.中国社会舆情与危机管理报告[M].北京:社会科学文献出版社,2013:276.
[3] 李文杰,化存才,何伟全,等.网络舆情信息的综合评价指标体系构建与模糊评判模型[J].情报科学,2015,33(9):93-99.
[4] 刘健,毕强,李瑞.微博舆情信息传播效果评价指标体系构建研究——基于模糊数据包络分析法[J].情报理论与实践,2016,39(12):31-38.
[5] 陈培友,侯甜甜.基于ANP-灰色模糊的社交网络舆情风险预警研究——以"重庆公交坠江事件"为例[J].情报科学,2019,37(5):115-120.
[6] 王宁,赵胜洋,单晓红.基于灰色系统理论的网络舆情预测与分级方法研究[J].情报理论与实践,2019,42(2):120-126.
[7] 于晶."从媒体到受众":政府危机传播效果的二级评估模式建构[J].新闻与传播研究,2012,19(2):52-58,111.
[8] 喻国明,李彪.舆情热点中政府危机干预的特点及借鉴意义[J].新闻与写作,2009(6):57-59.
[9] 刘泽照,张厚鼎.地方政府网络舆情回应行为研究——以人民网为例[J].情报杂志,2013,32(10):13-17.
[10] 兰月新,董希琳,陈成鑫.地方政府应对网络舆情能力评估和危机预警研究[J].现代情报,2012,32(5):8-12.
[11] SUNDAR S S. Multimedia effects on processing and perception of online news:a study of picture, audio, and video downloads[J]. Journalism & mass communication quarterly, 2000,77(3):480-499.
[12] MAYER R E, FENNELL S, FARMER L, et al. A personalization effect in multimedia learning:students learn better when words are in conversational style rather than formal style[J]. Journal of educational psychology, 2004, 96(2):389-395.