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The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities
The COVID-19 pandemic has resulted in cities implementing lockdown measures, causing unprecedented disruption (e.g. school/shop/office closures) to urban life often extending over months. With the spread of COVID-19 now being relatively contained, many cities have started to ease their lockdown rest...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631457/ https://www.ncbi.nlm.nih.gov/pubmed/36345535 http://dx.doi.org/10.1016/j.cities.2022.104054 |
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author | Chen, Yiqiao Niu, Haifeng Silva, Elisabete A. |
author_facet | Chen, Yiqiao Niu, Haifeng Silva, Elisabete A. |
author_sort | Chen, Yiqiao |
collection | PubMed |
description | The COVID-19 pandemic has resulted in cities implementing lockdown measures, causing unprecedented disruption (e.g. school/shop/office closures) to urban life often extending over months. With the spread of COVID-19 now being relatively contained, many cities have started to ease their lockdown restrictions by phases. Following the phased recovery strategy proposed by the UK government following the first national lockdown, this paper utilises Greater London as its case study, selecting three main reopening measures (i.e., schools, shops and hospitality reopening). This paper applies sentiment analysis and topic modelling to explore public opinions expressed via Twitter. Our findings reveal that public attention towards the reopening measures reached a peak before the date of policy implementation. The attitudes expressed in discussing reopening measures changed from negative to positive. Regarding the discussed topics related to reopening measures, we find that citizens are more sensitive to early-stage reopening than later ones. This study provides a time-sensitive approach for local authorities and city managers to rapidly sense public opinion using real-time social media data. Governments and policymakers can make use of the framework of sensing public opinion presented herein and utilise it in leading their post-lockdown cities into an adaptive, inclusive and smart recovery. |
format | Online Article Text |
id | pubmed-9631457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96314572022-11-03 The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities Chen, Yiqiao Niu, Haifeng Silva, Elisabete A. Cities Article The COVID-19 pandemic has resulted in cities implementing lockdown measures, causing unprecedented disruption (e.g. school/shop/office closures) to urban life often extending over months. With the spread of COVID-19 now being relatively contained, many cities have started to ease their lockdown restrictions by phases. Following the phased recovery strategy proposed by the UK government following the first national lockdown, this paper utilises Greater London as its case study, selecting three main reopening measures (i.e., schools, shops and hospitality reopening). This paper applies sentiment analysis and topic modelling to explore public opinions expressed via Twitter. Our findings reveal that public attention towards the reopening measures reached a peak before the date of policy implementation. The attitudes expressed in discussing reopening measures changed from negative to positive. Regarding the discussed topics related to reopening measures, we find that citizens are more sensitive to early-stage reopening than later ones. This study provides a time-sensitive approach for local authorities and city managers to rapidly sense public opinion using real-time social media data. Governments and policymakers can make use of the framework of sensing public opinion presented herein and utilise it in leading their post-lockdown cities into an adaptive, inclusive and smart recovery. The Authors. Published by Elsevier Ltd. 2023-01 2022-11-03 /pmc/articles/PMC9631457/ /pubmed/36345535 http://dx.doi.org/10.1016/j.cities.2022.104054 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Chen, Yiqiao Niu, Haifeng Silva, Elisabete A. The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities |
title | The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities |
title_full | The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities |
title_fullStr | The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities |
title_full_unstemmed | The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities |
title_short | The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities |
title_sort | road to recovery: sensing public opinion towards reopening measures with social media data in post-lockdown cities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631457/ https://www.ncbi.nlm.nih.gov/pubmed/36345535 http://dx.doi.org/10.1016/j.cities.2022.104054 |
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