基于社交媒体的人口和情感分析,用于灾害应对。

Q3 Medicine Journal of Emergency Management Pub Date : 2024-01-01 DOI:10.5055/jem.0781
Seungil Yum
{"title":"基于社交媒体的人口和情感分析,用于灾害应对。","authors":"Seungil Yum","doi":"10.5055/jem.0781","DOIUrl":null,"url":null,"abstract":"<p><p>This study explores disaster responses across the United States for Winter Storm Jaxon in 2018 by utilizing demographic and sentiment analysis for Twitter®. This study finds that people show highly fluctuated responses across the study periods and highest natural sentiment, followed by positive sentiment and negative sentiment. Also, some sociodemographic and Twitter variables, such as gender and long text, are strongly related to human sentiment, whereas other sociodemographic and Twitter variables, such as age and the higher number of retweets, are not associated with it. The results show that governments and disaster experts should consider a multitude of sociodemographic and Twitter variables to understand human responses and sentiment during natural disaster events.</p>","PeriodicalId":38336,"journal":{"name":"Journal of Emergency Management","volume":"22 1","pages":"89-99"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Social media-based demographic and sentiment analysis for disaster responses.\",\"authors\":\"Seungil Yum\",\"doi\":\"10.5055/jem.0781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study explores disaster responses across the United States for Winter Storm Jaxon in 2018 by utilizing demographic and sentiment analysis for Twitter®. This study finds that people show highly fluctuated responses across the study periods and highest natural sentiment, followed by positive sentiment and negative sentiment. Also, some sociodemographic and Twitter variables, such as gender and long text, are strongly related to human sentiment, whereas other sociodemographic and Twitter variables, such as age and the higher number of retweets, are not associated with it. The results show that governments and disaster experts should consider a multitude of sociodemographic and Twitter variables to understand human responses and sentiment during natural disaster events.</p>\",\"PeriodicalId\":38336,\"journal\":{\"name\":\"Journal of Emergency Management\",\"volume\":\"22 1\",\"pages\":\"89-99\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Emergency Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5055/jem.0781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Emergency Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5055/jem.0781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

摘要

本研究通过对 Twitter® 进行人口和情感分析,探讨美国各地对 2018 年冬季风暴 Jaxon 的灾难反应。本研究发现,人们在研究期间的反应波动很大,自然情绪最高,其次是积极情绪和消极情绪。此外,一些社会人口变量和 Twitter 变量(如性别和长文本)与人类情感密切相关,而其他社会人口变量和 Twitter 变量(如年龄和较高的转发次数)则与之无关。研究结果表明,政府和灾害专家应考虑多种社会人口变量和 Twitter 变量,以了解自然灾害事件中人类的反应和情绪。
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
Social media-based demographic and sentiment analysis for disaster responses.

This study explores disaster responses across the United States for Winter Storm Jaxon in 2018 by utilizing demographic and sentiment analysis for Twitter®. This study finds that people show highly fluctuated responses across the study periods and highest natural sentiment, followed by positive sentiment and negative sentiment. Also, some sociodemographic and Twitter variables, such as gender and long text, are strongly related to human sentiment, whereas other sociodemographic and Twitter variables, such as age and the higher number of retweets, are not associated with it. The results show that governments and disaster experts should consider a multitude of sociodemographic and Twitter variables to understand human responses and sentiment during natural disaster events.

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 Emergency Management
Journal of Emergency Management Medicine-Emergency Medicine
CiteScore
1.20
自引率
0.00%
发文量
67
期刊最新文献
United front: Emergency management managers, public health, and infection prevention. What's next for the disaster profession? A study of the opinions of local and state emergency managers and their recommendations for a more resilient future. A case study of university mass casualty simulation with high school deaf students who sign. A qualitative analysis of the effects of the COVID-19 response on low-income residents in Cameron County, Texas: Lessons for future pandemic response. Beirut 2020 explosion and health system response: An alarm for the dangerous consequences of Natech incidents in industrial cities.
×
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