The Communication Model of Negative Public Opinions of Corporate Based on Two-Layer Network

Shu-qiong Chen, Xiaoli Wang
{"title":"The Communication Model of Negative Public Opinions of Corporate Based on Two-Layer Network","authors":"Shu-qiong Chen, Xiaoli Wang","doi":"10.1145/3483845.3483868","DOIUrl":null,"url":null,"abstract":"In the era of new media, the spread of negative corporate public opinion in social networks has a significant influence on enterprises and society. In order to improve the ability of enterprises to respond to public opinion, it is important to study the evolutionary dissemination process of negative corporate public opinion. Firstly, BA network and ER network are used to simulate the online network and offline network. Then, we construct a model for the spread of negative corporate public opinion on both online and offline networks based on the real situation, and providing the corresponding mean field equation and solving the threshold value for the spread of negative corporate public opinion. Finally, the model is validated with the Samsung cell phone explosion incident and some response strategies are proposed based on image restoration theory. The results of the study show that the study of negative corporate opinion dissemination process in online and offline two-layer networks can better reflect the evolution of negative corporate opinion in real society than in single-layer networks; After the occurrence of negative public opinion events, enterprises should take appropriate response strategies in time, otherwise it will be counterproductive.","PeriodicalId":134636,"journal":{"name":"Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 2nd International Conference on Control, Robotics and Intelligent System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3483845.3483868","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In the era of new media, the spread of negative corporate public opinion in social networks has a significant influence on enterprises and society. In order to improve the ability of enterprises to respond to public opinion, it is important to study the evolutionary dissemination process of negative corporate public opinion. Firstly, BA network and ER network are used to simulate the online network and offline network. Then, we construct a model for the spread of negative corporate public opinion on both online and offline networks based on the real situation, and providing the corresponding mean field equation and solving the threshold value for the spread of negative corporate public opinion. Finally, the model is validated with the Samsung cell phone explosion incident and some response strategies are proposed based on image restoration theory. The results of the study show that the study of negative corporate opinion dissemination process in online and offline two-layer networks can better reflect the evolution of negative corporate opinion in real society than in single-layer networks; After the occurrence of negative public opinion events, enterprises should take appropriate response strategies in time, otherwise it will be counterproductive.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于双层网络的企业负面舆情传播模型
在新媒体时代,企业负面舆论在社交网络上的传播对企业和社会产生了重大影响。为了提高企业应对舆论的能力,研究负面企业舆论的演化传播过程十分重要。首先,采用BA网络和ER网络分别模拟了在线网络和离线网络。然后,根据实际情况构建了企业负面舆论在网络上和网络下的传播模型,并给出了企业负面舆论传播的均场方程,求解了企业负面舆论传播的阈值。最后,以三星手机爆炸事件为例对模型进行了验证,并提出了基于图像恢复理论的响应策略。研究结果表明,线上和线下两层网络对企业负面意见传播过程的研究比单层网络更能反映企业负面意见在现实社会中的演变;负面舆论事件发生后,企业应及时采取相应的应对策略,否则会适得其反。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Improved non-autoregressive dialog state tracking model Dynamic characteristics analysis of a new variable stiffness robot joint Interactive Intention Prediction Model for Humanoid Robot Based on Visual Features A propelled multiple fusion Deep Belief Network for weld defects detection Detection of Fatigued Face
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1