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Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets
BACKGROUND: During the COVID-19 pandemic, US public health authorities and county, state, and federal governments recommended or ordered certain preventative practices, such as wearing masks, to reduce the spread of the disease. However, individuals had divergent reactions to these preventive practi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722524/ https://www.ncbi.nlm.nih.gov/pubmed/35013722 http://dx.doi.org/10.2196/31671 |
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author | Kahanek, Alexander Yu, Xinchen Hong, Lingzi Cleveland, Ana Philbrick, Jodi |
author_facet | Kahanek, Alexander Yu, Xinchen Hong, Lingzi Cleveland, Ana Philbrick, Jodi |
author_sort | Kahanek, Alexander |
collection | PubMed |
description | BACKGROUND: During the COVID-19 pandemic, US public health authorities and county, state, and federal governments recommended or ordered certain preventative practices, such as wearing masks, to reduce the spread of the disease. However, individuals had divergent reactions to these preventive practices. OBJECTIVE: The purpose of this study was to understand the variations in public sentiment toward COVID-19 and the recommended or ordered preventive practices from the temporal and spatial perspectives, as well as how the variations in public sentiment are related to geographical and socioeconomic factors. METHODS: The authors leveraged machine learning methods to investigate public sentiment polarity in COVID-19–related tweets from January 21, 2020 to June 12, 2020. The study measured the temporal variations and spatial disparities in public sentiment toward both general COVID-19 topics and preventive practices in the United States. RESULTS: In the temporal analysis, we found a 4-stage pattern from high negative sentiment in the initial stage to decreasing and low negative sentiment in the second and third stages, to the rebound and increase in negative sentiment in the last stage. We also identified that public sentiment to preventive practices was significantly different in urban and rural areas, while poverty rate and unemployment rate were positively associated with negative sentiment to COVID-19 issues. CONCLUSIONS: The differences between public sentiment toward COVID-19 and the preventive practices imply that actions need to be taken to manage the initial and rebound stages in future pandemics. The urban and rural differences should be considered in terms of the communication strategies and decision making during a pandemic. This research also presents a framework to investigate time-sensitive public sentiment at the county and state levels, which could guide local and state governments and regional communities in making decisions and developing policies in crises. |
format | Online Article Text |
id | pubmed-8722524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-87225242022-01-06 Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets Kahanek, Alexander Yu, Xinchen Hong, Lingzi Cleveland, Ana Philbrick, Jodi JMIR Infodemiology Original Paper BACKGROUND: During the COVID-19 pandemic, US public health authorities and county, state, and federal governments recommended or ordered certain preventative practices, such as wearing masks, to reduce the spread of the disease. However, individuals had divergent reactions to these preventive practices. OBJECTIVE: The purpose of this study was to understand the variations in public sentiment toward COVID-19 and the recommended or ordered preventive practices from the temporal and spatial perspectives, as well as how the variations in public sentiment are related to geographical and socioeconomic factors. METHODS: The authors leveraged machine learning methods to investigate public sentiment polarity in COVID-19–related tweets from January 21, 2020 to June 12, 2020. The study measured the temporal variations and spatial disparities in public sentiment toward both general COVID-19 topics and preventive practices in the United States. RESULTS: In the temporal analysis, we found a 4-stage pattern from high negative sentiment in the initial stage to decreasing and low negative sentiment in the second and third stages, to the rebound and increase in negative sentiment in the last stage. We also identified that public sentiment to preventive practices was significantly different in urban and rural areas, while poverty rate and unemployment rate were positively associated with negative sentiment to COVID-19 issues. CONCLUSIONS: The differences between public sentiment toward COVID-19 and the preventive practices imply that actions need to be taken to manage the initial and rebound stages in future pandemics. The urban and rural differences should be considered in terms of the communication strategies and decision making during a pandemic. This research also presents a framework to investigate time-sensitive public sentiment at the county and state levels, which could guide local and state governments and regional communities in making decisions and developing policies in crises. JMIR Publications 2021-12-30 /pmc/articles/PMC8722524/ /pubmed/35013722 http://dx.doi.org/10.2196/31671 Text en ©Alexander Kahanek, Xinchen Yu, Lingzi Hong, Ana Cleveland, Jodi Philbrick. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 30.12.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Infodemiology, is properly cited. The complete bibliographic information, a link to the original publication on https://infodemiology.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Kahanek, Alexander Yu, Xinchen Hong, Lingzi Cleveland, Ana Philbrick, Jodi Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets |
title | Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets |
title_full | Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets |
title_fullStr | Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets |
title_full_unstemmed | Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets |
title_short | Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets |
title_sort | temporal variations and spatial disparities in public sentiment toward covid-19 and preventive practices in the united states: infodemiology study of tweets |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722524/ https://www.ncbi.nlm.nih.gov/pubmed/35013722 http://dx.doi.org/10.2196/31671 |
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