“美国的一切”州对COVID-19有什么看法?对俄亥俄州疫情的定量推特分析。

IF 2 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2022-01-01 Epub Date: 2021-04-05 DOI:10.1007/s42001-021-00111-1
Cantay Caliskan
{"title":"“美国的一切”州对COVID-19有什么看法?对俄亥俄州疫情的定量推特分析。","authors":"Cantay Caliskan","doi":"10.1007/s42001-021-00111-1","DOIUrl":null,"url":null,"abstract":"<p><p>COVID-19 has proven itself to be one of the most important events of the last two centuries. This defining moment in our lives has created wide-ranging discussions in many segments of our societies, both politically and socially. Over time, the pandemic has been associated with many social and political topics, as well as sentiments and emotions. Twitter offers a platform to understand these effects. The primary objective of this study is to capture the awareness and sentiment about COVID-19-related issues and to find how they relate to the number of cases and deaths in a representative region of the United States. The study uses a unique dataset consisting of over 46 million tweets from over 91,000 users in 88 counties of the state of Ohio, a state-of-the-art deep learning model to measure and detect awareness and emotions. The data collected is analyzed using OLS regression and System-GMM dynamic panel. Findings indicate that the pandemic has drastically changed the perception of the Republican party in the society. Individual motivations are strongly influenced by ideological choices and this ultimately affects individual pandemic-related outcomes. The paper contributes to the literature by expanding the knowledge on COVID-19 (i), offering a representative result for the United States by focusing on an \"average\" state like Ohio (ii), and incorporating the sentiment and emotions into the calculation of awareness (iii).</p>","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":" ","pages":"19-45"},"PeriodicalIF":2.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s42001-021-00111-1","citationCount":"4","resultStr":"{\"title\":\"How does \\\"A Bit of Everything American\\\" state feel about COVID-19? A quantitative Twitter analysis of the pandemic in Ohio.\",\"authors\":\"Cantay Caliskan\",\"doi\":\"10.1007/s42001-021-00111-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>COVID-19 has proven itself to be one of the most important events of the last two centuries. This defining moment in our lives has created wide-ranging discussions in many segments of our societies, both politically and socially. Over time, the pandemic has been associated with many social and political topics, as well as sentiments and emotions. Twitter offers a platform to understand these effects. The primary objective of this study is to capture the awareness and sentiment about COVID-19-related issues and to find how they relate to the number of cases and deaths in a representative region of the United States. The study uses a unique dataset consisting of over 46 million tweets from over 91,000 users in 88 counties of the state of Ohio, a state-of-the-art deep learning model to measure and detect awareness and emotions. The data collected is analyzed using OLS regression and System-GMM dynamic panel. Findings indicate that the pandemic has drastically changed the perception of the Republican party in the society. Individual motivations are strongly influenced by ideological choices and this ultimately affects individual pandemic-related outcomes. The paper contributes to the literature by expanding the knowledge on COVID-19 (i), offering a representative result for the United States by focusing on an \\\"average\\\" state like Ohio (ii), and incorporating the sentiment and emotions into the calculation of awareness (iii).</p>\",\"PeriodicalId\":29946,\"journal\":{\"name\":\"Journal of Computational Social Science\",\"volume\":\" \",\"pages\":\"19-45\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s42001-021-00111-1\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Social Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s42001-021-00111-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/4/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Social Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s42001-021-00111-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/4/5 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 4

摘要

事实证明,2019冠状病毒病是过去两个世纪最重要的事件之一。我们生活中的这一决定性时刻在我们社会的许多领域引发了广泛的讨论,包括政治和社会。随着时间的推移,这一流行病与许多社会和政治话题以及情绪和情绪联系在一起。Twitter提供了一个了解这些影响的平台。本研究的主要目的是捕捉对covid -19相关问题的认识和情绪,并找出它们与美国代表性地区的病例和死亡人数之间的关系。该研究使用了一个独特的数据集,包括来自俄亥俄州88个县的91,000多名用户的4600多万条推文,这是一个最先进的深度学习模型,用于测量和检测意识和情绪。采用OLS回归和System-GMM动态面板对收集的数据进行分析。调查结果显示,新冠疫情大大改变了社会对共和党的看法。个人动机受到意识形态选择的强烈影响,这最终影响到个人与大流行相关的结果。本文通过扩大对COVID-19的认识(i),通过关注俄亥俄州等“平均”州(ii),提供具有代表性的美国结果,并将情绪和情绪纳入意识的计算(iii),为文献做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

How does "A Bit of Everything American" state feel about COVID-19? A quantitative Twitter analysis of the pandemic in Ohio.

How does "A Bit of Everything American" state feel about COVID-19? A quantitative Twitter analysis of the pandemic in Ohio.

How does "A Bit of Everything American" state feel about COVID-19? A quantitative Twitter analysis of the pandemic in Ohio.

How does "A Bit of Everything American" state feel about COVID-19? A quantitative Twitter analysis of the pandemic in Ohio.

COVID-19 has proven itself to be one of the most important events of the last two centuries. This defining moment in our lives has created wide-ranging discussions in many segments of our societies, both politically and socially. Over time, the pandemic has been associated with many social and political topics, as well as sentiments and emotions. Twitter offers a platform to understand these effects. The primary objective of this study is to capture the awareness and sentiment about COVID-19-related issues and to find how they relate to the number of cases and deaths in a representative region of the United States. The study uses a unique dataset consisting of over 46 million tweets from over 91,000 users in 88 counties of the state of Ohio, a state-of-the-art deep learning model to measure and detect awareness and emotions. The data collected is analyzed using OLS regression and System-GMM dynamic panel. Findings indicate that the pandemic has drastically changed the perception of the Republican party in the society. Individual motivations are strongly influenced by ideological choices and this ultimately affects individual pandemic-related outcomes. The paper contributes to the literature by expanding the knowledge on COVID-19 (i), offering a representative result for the United States by focusing on an "average" state like Ohio (ii), and incorporating the sentiment and emotions into the calculation of awareness (iii).

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
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
×
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