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利用 Twitter 追踪非计划性学校关闭:佐治亚公立学校,2015-2017 年。

Using Twitter to Track Unplanned School Closures: Georgia Public Schools, 2015-17.

机构信息

Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia.

Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia.

出版信息

Disaster Med Public Health Prep. 2021 Oct;15(5):568-572. doi: 10.1017/dmp.2020.65. Epub 2020 May 14.

DOI:10.1017/dmp.2020.65
PMID:32406359
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7665976/
Abstract

OBJECTIVES

To aid emergency response, Centers for Disease Control and Prevention (CDC) researchers monitor unplanned school closures (USCs) by conducting online systematic searches (OSS) to identify relevant publicly available reports. We examined the added utility of analyzing Twitter data to improve USC monitoring.

METHODS

Georgia public school data were obtained from the National Center for Education Statistics. We identified school and district Twitter accounts with 1 or more tweets ever posted ("active"), and their USC-related tweets in the 2015-16 and 2016-17 school years. CDC researchers provided OSS-identified USC reports. Descriptive statistics, univariate, and multivariable logistic regression were computed.

RESULTS

A majority (1,864/2,299) of Georgia public schools had, or were in a district with, active Twitter accounts in 2017. Among these schools, 638 were identified with USCs in 2015-16 (Twitter only, 222; OSS only, 2015; both, 201) and 981 in 2016-17 (Twitter only, 178; OSS only, 107; both, 696). The marginal benefit of adding Twitter as a data source was an increase in the number of schools identified with USCs by 53% (222/416) in 2015-16 and 22% (178/803) in 2016-17.

CONCLUSIONS

Policy-makers may wish to consider the potential value of incorporating Twitter into existing USC monitoring systems.

摘要

目的

为了协助应急响应,疾病控制与预防中心(CDC)的研究人员通过进行在线系统搜索(OSS)来识别相关的公开可用报告,以监测非计划性学校关闭(USCs)。我们研究了分析 Twitter 数据以改善 USC 监测的附加效用。

方法

我们从国家教育统计中心获取了佐治亚州公立学校的数据。我们确定了具有 1 条或更多已发布推文的学校和地区 Twitter 账户(“活跃”),以及他们在 2015-16 和 2016-17 学年与 USC 相关的推文。CDC 研究人员提供了 OSS 确定的 USC 报告。计算了描述性统计、单变量和多变量逻辑回归。

结果

在 2017 年,佐治亚州的大多数(1864/2299)公立学校拥有或在一个地区拥有活跃的 Twitter 账户。在这些学校中,2015-16 年有 638 所学校被确定发生了 USC(仅通过 Twitter 确定的 222 所;仅通过 OSS 确定的 2015 所;两者均有确定的 201 所),2016-17 年有 981 所学校(仅通过 Twitter 确定的 178 所;仅通过 OSS 确定的 107 所;两者均有确定的 696 所)。将 Twitter 作为数据源添加的边际收益是,2015-16 年识别出 USC 的学校数量增加了 53%(222/416),2016-17 年增加了 22%(178/803)。

结论

决策者可能希望考虑将 Twitter 纳入现有的 USC 监测系统的潜在价值。