Analysis of Airline Sentiment Data: Does the social media image reflect real performance?

Haoran Zheng
{"title":"Analysis of Airline Sentiment Data: Does the social media image reflect real performance?","authors":"Haoran Zheng","doi":"10.33422/3rd.imeconf.2020.09.202","DOIUrl":null,"url":null,"abstract":"With the development of social media, increasingly more people express their feelings on social media (such as Twitter), which are a useful source of information e.g. for the airline companies which want to find out what causes negative sentiment about them and try to improve the communicated weaknesses. This paper aims to find out the variation in sentiment towards different airlines and check whether the Twitter perception of airlines reflects their “real” performances. The result suggests that Delta and Southwest airlines have a relatively good reputation, while US Airways has a bad reputation. By examining the reasons for negative sentiment, we find that Twitter ranking reflects the \"real\" ranking based on the Department of Transportation data closely for mishandled luggage and canceled flights, but considerably less closely for delayed flights. This demonstrates that Twitter can provide a good reflection of reality, but this is not always the case.","PeriodicalId":127642,"journal":{"name":"Proceedings of ‏The 3rd International Conference on Research in Management and Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of ‏The 3rd International Conference on Research in Management and Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33422/3rd.imeconf.2020.09.202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the development of social media, increasingly more people express their feelings on social media (such as Twitter), which are a useful source of information e.g. for the airline companies which want to find out what causes negative sentiment about them and try to improve the communicated weaknesses. This paper aims to find out the variation in sentiment towards different airlines and check whether the Twitter perception of airlines reflects their “real” performances. The result suggests that Delta and Southwest airlines have a relatively good reputation, while US Airways has a bad reputation. By examining the reasons for negative sentiment, we find that Twitter ranking reflects the "real" ranking based on the Department of Transportation data closely for mishandled luggage and canceled flights, but considerably less closely for delayed flights. This demonstrates that Twitter can provide a good reflection of reality, but this is not always the case.
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
航空公司情绪数据分析:社交媒体形象是否反映真实业绩?
随着社交媒体的发展,越来越多的人在社交媒体(如Twitter)上表达自己的感受,这是一个有用的信息来源,例如航空公司想要找出什么原因导致对他们的负面情绪,并试图改善沟通的弱点。本文旨在找出对不同航空公司的情绪差异,并检查航空公司的Twitter感知是否反映了他们的“真实”表现。结果表明,达美航空和西南航空公司的声誉相对较好,而全美航空公司的声誉较差。通过检查负面情绪的原因,我们发现Twitter排名反映了基于交通部数据的“真实”排名,这些数据与行李处理不当和航班取消密切相关,但与航班延误的密切程度要低得多。这表明Twitter可以很好地反映现实,但情况并非总是如此。
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
Evaluating the Effectiveness of Price Promotions Analysis of the risk Identification Stage in Project Management Management of Organizational and Technological Risks at the Stage of Preparation in Order to Minimize the Cost of Construction Activities Knowledge Networks, Proximity and Technology Dynamics of High-Tech Industries Baltic States Stock Market Listed Companies’ Absolute Value Indicators Analysis
×
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