• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

调查公众对学校饮用水含铅问题的看法:对环境健康危害的推特回应的混合方法分析。

Examining Public Perceptions about Lead in School Drinking Water: A Mixed-Methods Analysis of Twitter Response to an Environmental Health Hazard.

机构信息

Brown School, Washington University in St. Louis, St. Louis, MO 63130, USA.

Gateway to the Great Outdoors, Chicago, IL 60613, USA.

出版信息

Int J Environ Res Public Health. 2018 Jan 20;15(1):162. doi: 10.3390/ijerph15010162.

DOI:10.3390/ijerph15010162
PMID:29361676
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5800261/
Abstract

Exposure to lead has long been a community health concern in St. Louis, Missouri. The objective of this study was to examine public response to reports of elevated lead levels in school drinking water in St. Louis, Missouri via Twitter, a microblogging platform with over 320 million active users. We used a mixed-methods design to examine Twitter user status updates, known as "tweets," from 18 August to 31 December 2016. The number of tweets each day was recorded, and Twitter users were classified into five user types (General Public, Journalist/News, Health Professional/Academic, Politician/Government Official, and Non-Governmental Organization). A total of 492 tweets were identified during the study period. The majority of discourse on Twitter occurred during the two-week period after initial media reports and was driven by members of the General Public. Thematic analysis of tweets revealed four themes: Information Sharing, Health Concerns, Sociodemographic Disparities, and Outrage. Twitter users characterized lead in school drinking water as an issue of environmental inequity. The findings of this study provide evidence that social media platforms can be utilized as valuable tools for public health researchers and practitioners to gauge public sentiment about environmental health issues, identify emerging community concerns, and inform future communication and research strategies regarding environmental health hazards.

摘要

长期以来,密苏里州圣路易斯市的铅暴露一直是社区健康关注的焦点。本研究的目的是通过微博客平台 Twitter 来研究公众对圣路易斯市学校饮用水中铅含量升高的报告的反应,该平台拥有超过 3.2 亿活跃用户。我们采用混合方法设计来检查 2016 年 8 月 18 日至 12 月 31 日期间的 Twitter 用户状态更新,即“推文”。每天记录推文数量,并将 Twitter 用户分为五类(普通公众、记者/新闻、健康专业人员/学者、政治家/政府官员和非政府组织)。在研究期间共确定了 492 条推文。Twitter 上的大部分讨论都发生在最初的媒体报道后的两周内,主要由普通公众推动。推文的主题分析揭示了四个主题:信息共享、健康关注、社会人口差异和愤怒。Twitter 用户将学校饮用水中的铅描述为环境不公平问题。这项研究的结果表明,社交媒体平台可以作为公共卫生研究人员和从业者的有价值工具,用于衡量公众对环境健康问题的看法,识别新出现的社区关注问题,并为环境健康危害的未来沟通和研究策略提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7189/5800261/49d358fa5142/ijerph-15-00162-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7189/5800261/adb331453914/ijerph-15-00162-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7189/5800261/49d358fa5142/ijerph-15-00162-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7189/5800261/adb331453914/ijerph-15-00162-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7189/5800261/49d358fa5142/ijerph-15-00162-g002.jpg

相似文献

1
Examining Public Perceptions about Lead in School Drinking Water: A Mixed-Methods Analysis of Twitter Response to an Environmental Health Hazard.调查公众对学校饮用水含铅问题的看法:对环境健康危害的推特回应的混合方法分析。
Int J Environ Res Public Health. 2018 Jan 20;15(1):162. doi: 10.3390/ijerph15010162.
2
Social Listening: A Content Analysis of E-Cigarette Discussions on Twitter.社交倾听:对推特上电子烟讨论的内容分析
J Med Internet Res. 2015 Oct 27;17(10):e243. doi: 10.2196/jmir.4969.
3
Digital Surveillance for Monitoring Environmental Health Threats: A Case Study Capturing Public Opinion from Twitter about the 2019 Chennai Water Crisis.数字监控在环境健康威胁监测中的应用:以 2019 年钦奈水危机中从 Twitter 上获取公众意见为例的研究。
Int J Environ Res Public Health. 2020 Jul 14;17(14):5077. doi: 10.3390/ijerph17145077.
4
COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.新冠疫情与5G阴谋论:基于推特数据的社交网络分析
J Med Internet Res. 2020 May 6;22(5):e19458. doi: 10.2196/19458.
5
The pattern and use of Twitter among dental schools in Saudi Arabia.沙特阿拉伯牙科学院的 Twitter 使用模式和情况。
PLoS One. 2022 Sep 8;17(9):e0272628. doi: 10.1371/journal.pone.0272628. eCollection 2022.
6
Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach.理解推特上的#世界环境日用户意见:一种基于主题的情感分析方法。
Int J Environ Res Public Health. 2018 Nov 13;15(11):2537. doi: 10.3390/ijerph15112537.
7
Social Media and Research Publication Activity During Early Stages of the COVID-19 Pandemic: Longitudinal Trend Analysis.社交媒体与 COVID-19 大流行早期阶段的研究出版活动:纵向趋势分析。
J Med Internet Res. 2021 Jun 17;23(6):e26956. doi: 10.2196/26956.
8
Perceptions of Menthol Cigarettes Among Twitter Users: Content and Sentiment Analysis.推特用户对薄荷醇香烟的认知:内容与情感分析
J Med Internet Res. 2017 Feb 27;19(2):e56. doi: 10.2196/jmir.5694.
9
Current Social Media Conversations about Genetics and Genomics in Health: A Twitter-Based Analysis.当前社交媒体上关于健康领域遗传学和基因组学的对话:基于推特的分析
Public Health Genomics. 2018;21(1-2):93-99. doi: 10.1159/000494381. Epub 2018 Nov 22.
10
Using Twitter Comments to Understand People's Experiences of UK Health Care During the COVID-19 Pandemic: Thematic and Sentiment Analysis.利用推特评论了解新冠疫情期间英国人对英国医疗保健的体验:主题和情感分析。
J Med Internet Res. 2021 Oct 25;23(10):e31101. doi: 10.2196/31101.

引用本文的文献

1
Exploring Iranian sentiments on the Paris Agreement: Insights from Twitter.探索伊朗人对《巴黎协定》的看法:来自推特的见解。
Heliyon. 2025 Feb 14;11(4):e42716. doi: 10.1016/j.heliyon.2025.e42716. eCollection 2025 Feb 28.
2
Let's talk about PFAS: Inconsistent public awareness about PFAS and its sources in the United States.让我们来谈谈全氟和多氟烷基物质(PFAS):在美国,公众对 PFAS 及其来源的认识存在不一致性。
PLoS One. 2023 Nov 16;18(11):e0294134. doi: 10.1371/journal.pone.0294134. eCollection 2023.
3
Environmental health perceptions of urban youth from low-income communities: A qualitative photovoice study and framework.

本文引用的文献

1
Recognizing Drinking Water Pipes as Community Health Hazards.将饮用水管道视为社区健康危害。
J Chem Educ. 2016 Apr 12;93(4):581-582. doi: 10.1021/acs.jchemed.6b00218.
2
An Update on Childhood Lead Poisoning.儿童铅中毒最新情况
Clin Pediatr Emerg Med. 2017 Sep;18(3):181-192. doi: 10.1016/j.cpem.2017.07.010.
3
Public sentiment and discourse about Zika virus on Instagram.Instagram上关于寨卡病毒的公众情绪与讨论。
城市低收入社区青年的环境健康感知:一项定性摄影研究和框架。
Health Expect. 2023 Oct;26(5):1832-1842. doi: 10.1111/hex.13776. Epub 2023 Jun 14.
4
A Narrative Literature Review of Natural Language Processing Applied to the Occupational Exposome.自然语言处理在职业外核组学中的应用的叙事文献综述。
Int J Environ Res Public Health. 2022 Jul 13;19(14):8544. doi: 10.3390/ijerph19148544.
5
The COVID-19 Pandemic as a Threat Multiplier for Childhood Health Disparities: Evidence from St. Louis, MO.新冠疫情成为儿童健康差距的威胁倍增器:来自密苏里州圣路易斯市的证据
J Urban Health. 2022 Apr;99(2):208-217. doi: 10.1007/s11524-022-00616-8. Epub 2022 Mar 29.
6
Emergency Medicine Influencers' Twitter Use During the COVID-19 Pandemic: A Mixed-methods Analysis.新冠疫情期间急诊医学有影响力人士的推特使用情况:一项混合方法分析
West J Emerg Med. 2021 Mar 22;22(3):710-718. doi: 10.5811/westjem.2020.12.49213.
7
An Analysis of the Educational and Health-Related Benefits of Nature-Based Environmental Education in Low-Income Black and Hispanic Children.对低收入黑人和西班牙裔儿童基于自然的环境教育的教育及健康相关益处的分析
Health Equity. 2020 May 18;4(1):198-210. doi: 10.1089/heq.2019.0118. eCollection 2020.
8
Gaining a deeper understanding of nutrition using social networks and user-generated content.利用社交网络和用户生成内容更深入地了解营养。
Internet Interv. 2020 Mar 19;20:100312. doi: 10.1016/j.invent.2020.100312. eCollection 2020 Apr.
9
Psychological Disorder Identifying Method Based on Emotion Perception over Social Networks.基于社交媒体情绪感知的心理障碍识别方法
Int J Environ Res Public Health. 2019 Mar 16;16(6):953. doi: 10.3390/ijerph16060953.
10
Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach.理解推特上的#世界环境日用户意见:一种基于主题的情感分析方法。
Int J Environ Res Public Health. 2018 Nov 13;15(11):2537. doi: 10.3390/ijerph15112537.
Public Health. 2017 Sep;150:170-175. doi: 10.1016/j.puhe.2017.07.015. Epub 2017 Aug 12.
4
Flint Water Crisis Caused By Interrupted Corrosion Control: Investigating "Ground Zero" Home.弗林特水危机由中断的腐蚀控制引起:调查“零号地带”住宅。
Environ Sci Technol. 2017 Feb 21;51(4):2007-2014. doi: 10.1021/acs.est.6b04034. Epub 2017 Feb 1.
5
Twitter as a Tool for Health Research: A Systematic Review.推特作为健康研究工具:一项系统综述
Am J Public Health. 2017 Jan;107(1):e1-e8. doi: 10.2105/AJPH.2016.303512. Epub 2016 Nov 17.
6
Chinese Public Attention to the Outbreak of Ebola in West Africa: Evidence from the Online Big Data Platform.中国公众对西非埃博拉疫情的关注:来自在线大数据平台的证据
Int J Environ Res Public Health. 2016 Aug 4;13(8):780. doi: 10.3390/ijerph13080780.
7
Lead Contamination in Flint--An Abject Failure to Protect Public Health.弗林特的铅污染——保护公众健康的彻底失败。
N Engl J Med. 2016 Mar 24;374(12):1101-3. doi: 10.1056/NEJMp1601013. Epub 2016 Feb 10.
8
Elevated Blood Lead Levels in Children Associated With the Flint Drinking Water Crisis: A Spatial Analysis of Risk and Public Health Response.与弗林特饮用水危机相关的儿童血铅水平升高:风险及公共卫生应对措施的空间分析
Am J Public Health. 2016 Feb;106(2):283-90. doi: 10.2105/AJPH.2015.303003. Epub 2015 Dec 21.
9
Methodological considerations in analyzing Twitter data.分析推特数据时的方法学考量
J Natl Cancer Inst Monogr. 2013 Dec;2013(47):140-6. doi: 10.1093/jncimonographs/lgt026.
10
Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial.计算观测数据的评分者间信度:概述与教程
Tutor Quant Methods Psychol. 2012;8(1):23-34. doi: 10.20982/tqmp.08.1.p023.