我的社交媒体烧了吗?-识别Twitter上与公司相关的在线Firestorms的早期检测功能

Q1 Social Sciences Online Social Networks and Media Pub Date : 2021-09-01 DOI:10.1016/j.osnem.2021.100151
Kevin Koch, Alexander Dippel, Matthias Schumann
{"title":"我的社交媒体烧了吗?-识别Twitter上与公司相关的在线Firestorms的早期检测功能","authors":"Kevin Koch,&nbsp;Alexander Dippel,&nbsp;Matthias Schumann","doi":"10.1016/j.osnem.2021.100151","DOIUrl":null,"url":null,"abstract":"<div><p><span>Online firestorms pose a serious threat to companies and cause spontaneous information asymmetry between companies and </span>social media users<span>, which is part of the principal-agent theory. Corporate crisis management has already developed strategies to deal with firestorms, but these strategies are more effective if the company identifies a firestorm at an early stage. Therefore, we first identify literature-based characteristics of firestorms and quantify these using data-driven features in a multiple-case study approach based on Twitter data. Secondly, we identify per case the beginning of the firestorm and days with the least fluctuation in the number of posts as reference days. Finally, we compare the features between the starting points and the reference days to determine which features are significantly different. We could identify 24 features that change significantly at the beginning of a firestorm. This enables us to determine which features a company must pay particular attention to in order to detect a firestorm at an early stage. Likewise, we discuss these features in the context of the principal-agent theory with the use of social synchrony and crowd psychology to show how these features change information diffusion and contribute to information asymmetry.</span></p></div>","PeriodicalId":52228,"journal":{"name":"Online Social Networks and Media","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.osnem.2021.100151","citationCount":"6","resultStr":"{\"title\":\"Does my Social Media Burn? – Identify Features for the Early Detection of Company-related Online Firestorms on Twitter\",\"authors\":\"Kevin Koch,&nbsp;Alexander Dippel,&nbsp;Matthias Schumann\",\"doi\":\"10.1016/j.osnem.2021.100151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>Online firestorms pose a serious threat to companies and cause spontaneous information asymmetry between companies and </span>social media users<span>, which is part of the principal-agent theory. Corporate crisis management has already developed strategies to deal with firestorms, but these strategies are more effective if the company identifies a firestorm at an early stage. Therefore, we first identify literature-based characteristics of firestorms and quantify these using data-driven features in a multiple-case study approach based on Twitter data. Secondly, we identify per case the beginning of the firestorm and days with the least fluctuation in the number of posts as reference days. Finally, we compare the features between the starting points and the reference days to determine which features are significantly different. We could identify 24 features that change significantly at the beginning of a firestorm. This enables us to determine which features a company must pay particular attention to in order to detect a firestorm at an early stage. Likewise, we discuss these features in the context of the principal-agent theory with the use of social synchrony and crowd psychology to show how these features change information diffusion and contribute to information asymmetry.</span></p></div>\",\"PeriodicalId\":52228,\"journal\":{\"name\":\"Online Social Networks and Media\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.osnem.2021.100151\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Online Social Networks and Media\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468696421000331\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Online Social Networks and Media","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468696421000331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 6

摘要

网络风暴对企业构成严重威胁,导致企业与社交媒体用户之间自发的信息不对称,这是委托代理理论的一部分。企业危机管理已经制定了应对火灾风暴的策略,但如果公司在早期阶段识别出火灾风暴,这些策略会更有效。因此,我们首先确定基于文献的火灾风暴特征,并在基于Twitter数据的多案例研究方法中使用数据驱动特征对这些特征进行量化。其次,我们确定每个案例的火风暴开始和帖子数量波动最小的日子作为参考日。最后,我们比较起始点和参考日之间的特征,以确定哪些特征显著不同。我们可以识别出24个特征在风暴开始时发生了显著变化。这使我们能够确定公司必须特别注意哪些特征,以便在早期阶段发现风暴。同样,我们在委托代理理论的背景下讨论了这些特征,并使用社会同步和群体心理学来展示这些特征如何改变信息扩散并导致信息不对称。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Does my Social Media Burn? – Identify Features for the Early Detection of Company-related Online Firestorms on Twitter

Online firestorms pose a serious threat to companies and cause spontaneous information asymmetry between companies and social media users, which is part of the principal-agent theory. Corporate crisis management has already developed strategies to deal with firestorms, but these strategies are more effective if the company identifies a firestorm at an early stage. Therefore, we first identify literature-based characteristics of firestorms and quantify these using data-driven features in a multiple-case study approach based on Twitter data. Secondly, we identify per case the beginning of the firestorm and days with the least fluctuation in the number of posts as reference days. Finally, we compare the features between the starting points and the reference days to determine which features are significantly different. We could identify 24 features that change significantly at the beginning of a firestorm. This enables us to determine which features a company must pay particular attention to in order to detect a firestorm at an early stage. Likewise, we discuss these features in the context of the principal-agent theory with the use of social synchrony and crowd psychology to show how these features change information diffusion and contribute to information asymmetry.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
期刊最新文献
How does user-generated content on Social Media affect stock predictions? A case study on GameStop Measuring centralization of online platforms through size and interconnection of communities Crowdsourcing the Mitigation of disinformation and misinformation: The case of spontaneous community-based moderation on Reddit GASCOM: Graph-based Attentive Semantic Context Modeling for Online Conversation Understanding The influence of coordinated behavior on toxicity
×
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