[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.
Zhou Xin
,
Li Rui
,
Huang Wei
. Research on Crisis Response Mechanism and Risk Classification of Multimedia Network Public Opinion[J]. Library and Information Service, 2019
, 63(20)
: 6
-16
.
DOI: 10.13266/j.issn.0252-3116.2019.20.001
[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.