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Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data
The Chinese government has launched a digital health code system to detect people potentially exposed to the coronavirus 2019 (COVID-19) disease and to curb its spread. Citizens are required to show the health code on their smartphones when using public transport. However, many seniors are not allow...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918804/ https://www.ncbi.nlm.nih.gov/pubmed/33670271 http://dx.doi.org/10.3390/ijerph18041756 |
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author | Liu, Xinghua Ye, Qian Li, Ye Fan, Jing Tao, Yue |
author_facet | Liu, Xinghua Ye, Qian Li, Ye Fan, Jing Tao, Yue |
author_sort | Liu, Xinghua |
collection | PubMed |
description | The Chinese government has launched a digital health code system to detect people potentially exposed to the coronavirus 2019 (COVID-19) disease and to curb its spread. Citizens are required to show the health code on their smartphones when using public transport. However, many seniors are not allowed to use public transport due to their difficulties in obtaining health codes, leading to widespread debates about these unfair events. Traditionally, public perceptions and attitudes toward such unfair events are investigated using analytical methods based on interviews or questionnaires. This study crawled seven-month messages from Sina Weibo, the Chinese version of Twitter, and developed a hybrid approach integrating term-frequency–inverse-document-frequency, latent Dirichlet allocation, and sentiment classification. Results indicate that a rumor about the unfair treatment of elderly travelers triggered public concerns. Primary subjects of concern were the status quo of elderly travelers, the provision of transport services, and unfair event descriptions. Following the government’s responses, people still had negative attitudes toward transport services, while they became more positive about the status quo of elderly travelers. These findings will guide government authorities to explore new forms of automated social control and to improve transport policies in terms of equity and fairness in future pandemics. |
format | Online Article Text |
id | pubmed-7918804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79188042021-03-02 Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data Liu, Xinghua Ye, Qian Li, Ye Fan, Jing Tao, Yue Int J Environ Res Public Health Article The Chinese government has launched a digital health code system to detect people potentially exposed to the coronavirus 2019 (COVID-19) disease and to curb its spread. Citizens are required to show the health code on their smartphones when using public transport. However, many seniors are not allowed to use public transport due to their difficulties in obtaining health codes, leading to widespread debates about these unfair events. Traditionally, public perceptions and attitudes toward such unfair events are investigated using analytical methods based on interviews or questionnaires. This study crawled seven-month messages from Sina Weibo, the Chinese version of Twitter, and developed a hybrid approach integrating term-frequency–inverse-document-frequency, latent Dirichlet allocation, and sentiment classification. Results indicate that a rumor about the unfair treatment of elderly travelers triggered public concerns. Primary subjects of concern were the status quo of elderly travelers, the provision of transport services, and unfair event descriptions. Following the government’s responses, people still had negative attitudes toward transport services, while they became more positive about the status quo of elderly travelers. These findings will guide government authorities to explore new forms of automated social control and to improve transport policies in terms of equity and fairness in future pandemics. MDPI 2021-02-11 2021-02 /pmc/articles/PMC7918804/ /pubmed/33670271 http://dx.doi.org/10.3390/ijerph18041756 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Xinghua Ye, Qian Li, Ye Fan, Jing Tao, Yue Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data |
title | Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data |
title_full | Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data |
title_fullStr | Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data |
title_full_unstemmed | Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data |
title_short | Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data |
title_sort | examining public concerns and attitudes toward unfair events involving elderly travelers during the covid-19 pandemic using weibo data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918804/ https://www.ncbi.nlm.nih.gov/pubmed/33670271 http://dx.doi.org/10.3390/ijerph18041756 |
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