TY - JOUR
T1 - Using Twitter to Track Unplanned School Closures
T2 - Georgia Public Schools, 2015-17
AU - Ahweyevu, Jennifer O.
AU - Chukwudebe, Ngozi P.
AU - Buchanan, Brittany M.
AU - Yin, Jingjing
AU - Adhikari, Bishwa B.
AU - Zhou, Xiaolu
AU - Tse, Zion Tsz Ho
AU - Chowell, Gerardo
AU - Meltzer, Martin I.
AU - Fung, Isaac Chun Hai
N1 - Publisher Copyright:
© 2020 Society for Disaster Medicine and Public Health, Inc..
PY - 2021/10/14
Y1 - 2021/10/14
N2 - 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.
AB - 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.
KW - digital health
KW - public health surveillance
KW - social distancing
KW - social media
UR - http://www.scopus.com/inward/record.url?scp=85085021257&partnerID=8YFLogxK
U2 - 10.1017/dmp.2020.65
DO - 10.1017/dmp.2020.65
M3 - Article
SN - 1935-7893
VL - 15
SP - 568
EP - 572
JO - Disaster Medicine and Public Health Preparedness
JF - Disaster Medicine and Public Health Preparedness
IS - 5
ER -
