探索公众对政府COVID-19大流行政策的反应

IF 0.7 Q3 COMMUNICATION
Brenna Drummond, Aysun Bozanta
{"title":"探索公众对政府COVID-19大流行政策的反应","authors":"Brenna Drummond, Aysun Bozanta","doi":"10.30935/ojcmt/11829","DOIUrl":null,"url":null,"abstract":"The ongoing pandemic of coronavirus disease 2019 (COVID-19) has challenged governments worldwide and approaches to combating the spread and maintaining livelihoods have ranged significantly. The purpose of the study is to a) investigate whether social media, specifically Twitter, can be used to identify topics of discussion regarding governments’ COVID-19 policies, and;b) whether those discussions can be interpreted in a way that can support governments in making policy decisions. Real-time public responses to these policies are a matter of interest, as understanding the content of discussions and the attitudes expressed towards government approaches can support the development of more grounded solutions for large-scale policy issues. Latent Dirichlet Allocation (LDA) is used to identify topics of discussion alongside Valence Aware Dictionary for sEntiment Reasoning (VADER) sentiment analyzer. Text data from two different jurisdictions are used and examined side by side. The Oxford COVID-19 Government Response Tracker (OxCGRT) is used to standardize policy discussions. The results of the study found that: a) Individuals tweeted most frequently and most passionately about case and death rates in their jurisdictions. Particularly about the rates with respect to vulnerable populations, such as those in long term care, nursing homes, and health workers, and b) Tweets expressed frustrations with the communication, length of implementation, or lack of rationale behind policies, suggesting the way the policy is communicated and delivered impacts individuals’ sentiments. © 2022 by authors.","PeriodicalId":42941,"journal":{"name":"Online Journal of Communication and Media Technologies","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Exploring Public Responses to Government’s COVID-19 Pandemic Policies\",\"authors\":\"Brenna Drummond, Aysun Bozanta\",\"doi\":\"10.30935/ojcmt/11829\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ongoing pandemic of coronavirus disease 2019 (COVID-19) has challenged governments worldwide and approaches to combating the spread and maintaining livelihoods have ranged significantly. The purpose of the study is to a) investigate whether social media, specifically Twitter, can be used to identify topics of discussion regarding governments’ COVID-19 policies, and;b) whether those discussions can be interpreted in a way that can support governments in making policy decisions. Real-time public responses to these policies are a matter of interest, as understanding the content of discussions and the attitudes expressed towards government approaches can support the development of more grounded solutions for large-scale policy issues. Latent Dirichlet Allocation (LDA) is used to identify topics of discussion alongside Valence Aware Dictionary for sEntiment Reasoning (VADER) sentiment analyzer. Text data from two different jurisdictions are used and examined side by side. The Oxford COVID-19 Government Response Tracker (OxCGRT) is used to standardize policy discussions. The results of the study found that: a) Individuals tweeted most frequently and most passionately about case and death rates in their jurisdictions. Particularly about the rates with respect to vulnerable populations, such as those in long term care, nursing homes, and health workers, and b) Tweets expressed frustrations with the communication, length of implementation, or lack of rationale behind policies, suggesting the way the policy is communicated and delivered impacts individuals’ sentiments. © 2022 by authors.\",\"PeriodicalId\":42941,\"journal\":{\"name\":\"Online Journal of Communication and Media Technologies\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Online Journal of Communication and Media Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30935/ojcmt/11829\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Online Journal of Communication and Media Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30935/ojcmt/11829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 1

摘要

持续的2019冠状病毒病(COVID-19)大流行给世界各国政府带来了挑战,各国政府应对疫情传播和维持生计的方法各不相同。该研究的目的是:a)调查社交媒体,特别是推特,是否可以用来确定有关政府COVID-19政策的讨论主题;b)这些讨论是否可以以一种支持政府制定政策决策的方式进行解释。公众对这些政策的实时反应是一件有趣的事情,因为了解讨论的内容和对政府方法表达的态度可以支持为大规模政策问题制定更有根据的解决方案。潜在狄利克雷分配(LDA)用于识别讨论主题,以及情感推理的价感知词典(VADER)情感分析器。来自两个不同司法管辖区的文本数据被并排使用和检查。牛津COVID-19政府反应追踪器(OxCGRT)用于规范政策讨论。研究结果发现:a)个人在推特上最频繁、最热情地谈论他们管辖范围内的病例和死亡率。特别是关于弱势群体(如长期护理、养老院和卫生工作者)的比率,以及b)推文表达了对沟通、实施时间长短或政策背后缺乏理由的失望,这表明政策的沟通和传递方式影响了个人的情绪。©2022作者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring Public Responses to Government’s COVID-19 Pandemic Policies
The ongoing pandemic of coronavirus disease 2019 (COVID-19) has challenged governments worldwide and approaches to combating the spread and maintaining livelihoods have ranged significantly. The purpose of the study is to a) investigate whether social media, specifically Twitter, can be used to identify topics of discussion regarding governments’ COVID-19 policies, and;b) whether those discussions can be interpreted in a way that can support governments in making policy decisions. Real-time public responses to these policies are a matter of interest, as understanding the content of discussions and the attitudes expressed towards government approaches can support the development of more grounded solutions for large-scale policy issues. Latent Dirichlet Allocation (LDA) is used to identify topics of discussion alongside Valence Aware Dictionary for sEntiment Reasoning (VADER) sentiment analyzer. Text data from two different jurisdictions are used and examined side by side. The Oxford COVID-19 Government Response Tracker (OxCGRT) is used to standardize policy discussions. The results of the study found that: a) Individuals tweeted most frequently and most passionately about case and death rates in their jurisdictions. Particularly about the rates with respect to vulnerable populations, such as those in long term care, nursing homes, and health workers, and b) Tweets expressed frustrations with the communication, length of implementation, or lack of rationale behind policies, suggesting the way the policy is communicated and delivered impacts individuals’ sentiments. © 2022 by authors.
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
CiteScore
3.40
自引率
5.00%
发文量
40
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信