Twitter Sentiment Analysis During Unlock Period of COVID-19

Swati Sharma, Aryaman Sharma
{"title":"Twitter Sentiment Analysis During Unlock Period of COVID-19","authors":"Swati Sharma, Aryaman Sharma","doi":"10.1109/PDGC50313.2020.9315773","DOIUrl":null,"url":null,"abstract":"The pandemic has hit the individuals at both personal, social and professional front triggering emotional crisis leading to stress, anxiety and other related problems. However, some countries are now easing down on restrictions by going from lock down to unlocking in a phased manner. As life springs back to action the sentiments and emotions of people are bound to change. It therefore becomes imperative to understand the emotions and sentiments of people after seven months of outbreak when the people are more informed about the nature of disease, steps for prevention and also have hope for a vaccine coming up in near future. The study analyses the sentiments of the people from the USA and India by text mining using R Studio. The study has various implications for academicians as it adds to the existing knowledge pool. The findings provide guidance to the policy makers to tailor their support policies in response to the emotional state of their people and also assists the marketers to tailor the communication strategies in the light of the emotional state of the target market.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDGC50313.2020.9315773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

The pandemic has hit the individuals at both personal, social and professional front triggering emotional crisis leading to stress, anxiety and other related problems. However, some countries are now easing down on restrictions by going from lock down to unlocking in a phased manner. As life springs back to action the sentiments and emotions of people are bound to change. It therefore becomes imperative to understand the emotions and sentiments of people after seven months of outbreak when the people are more informed about the nature of disease, steps for prevention and also have hope for a vaccine coming up in near future. The study analyses the sentiments of the people from the USA and India by text mining using R Studio. The study has various implications for academicians as it adds to the existing knowledge pool. The findings provide guidance to the policy makers to tailor their support policies in response to the emotional state of their people and also assists the marketers to tailor the communication strategies in the light of the emotional state of the target market.
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
COVID-19解锁期间的推特情绪分析
疫情对个人、社会和职业都造成了冲击,引发了情绪危机,导致压力、焦虑和其他相关问题。然而,一些国家正在逐步放宽限制,从封锁到分阶段开放。随着生活重新开始行动,人们的情绪和情感必然会发生变化。因此,在疫情爆发7个月后,人们对疾病的性质、预防措施有了更多的了解,并对不久的将来出现疫苗抱有希望,了解人们的情绪和情绪变得至关重要。该研究通过使用R Studio进行文本挖掘,分析了来自美国和印度的人们的情绪。这项研究对学者们有各种各样的影响,因为它增加了现有的知识库。研究结果可以指导政策制定者根据目标市场的情绪状态制定相应的支持政策,也可以帮助营销人员根据目标市场的情绪状态制定相应的传播策略。
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
Message Data Analysis of Various Terrorism Activities Using Big Data Approaches on Global Terrorism Database A Convolutional Neural Network Approach for The Diagnosis of Breast Cancer Color Fading: Variation of Colorimetric Parameters with Spectral Reflectance Automatic Rumour Detection Model on Social Media
×
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