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Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China

The outbreak of a novel coronavirus pneumonia (COVID-19), wherein more than 200 million people have been infected and millions have died, poses a great threat to achieving the United Nations 2030 sustainable development goal (SDGs). Based on the Baidu index of ’novel coronavirus’, this paper analyse...

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Autores principales: Guo, Xiaojia, Zhang, Jing, Wu, Xueling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445458/
https://www.ncbi.nlm.nih.gov/pubmed/34529727
http://dx.doi.org/10.1371/journal.pone.0257291
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author Guo, Xiaojia
Zhang, Jing
Wu, Xueling
author_facet Guo, Xiaojia
Zhang, Jing
Wu, Xueling
author_sort Guo, Xiaojia
collection PubMed
description The outbreak of a novel coronavirus pneumonia (COVID-19), wherein more than 200 million people have been infected and millions have died, poses a great threat to achieving the United Nations 2030 sustainable development goal (SDGs). Based on the Baidu index of ’novel coronavirus’, this paper analyses the spatial and temporal characteristics of and factors that influenced the attention network for COVID-19 from January 9, 2020, to April 15, 2020. The study found that (1) Temporally, the attention in the new coronavirus network showed an upward trend from January 9 to January 29, with the largest increase from January 23 to January 29 and a peak on January 29, and then a slow downward trend. The level of attention in the new coronavirus network was basically flat when comparing January 22 and March 4. (2) Spatially, first, from the perspective of regional differences, the network attention in the eastern and central regions decreased in turn. The network users in the eastern region exhibited the highest attention to the new coronavirus, especially in Guangdong, Shandong, Jiangsu and other provinces and cities. The network attention in Tibet, Xinjiang, Qinghai and Ningxia in the western region was the lowest in terms of the national network attention. Second, from the perspective of interprovincial differences, the attention in the new coronavirus network was highly consistent with the Hu Huanyong line of China’s population boundary. The east of the Hu Huanyong line is densely populated, and the network showed high concern, mostly ranking at the third to fifth levels. (3) The number of Internet users in the information technology field, the population, and the culture and age characteristics of individuals are important factors that influence the novel coronavirus attention network.
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spelling pubmed-84454582021-09-17 Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China Guo, Xiaojia Zhang, Jing Wu, Xueling PLoS One Research Article The outbreak of a novel coronavirus pneumonia (COVID-19), wherein more than 200 million people have been infected and millions have died, poses a great threat to achieving the United Nations 2030 sustainable development goal (SDGs). Based on the Baidu index of ’novel coronavirus’, this paper analyses the spatial and temporal characteristics of and factors that influenced the attention network for COVID-19 from January 9, 2020, to April 15, 2020. The study found that (1) Temporally, the attention in the new coronavirus network showed an upward trend from January 9 to January 29, with the largest increase from January 23 to January 29 and a peak on January 29, and then a slow downward trend. The level of attention in the new coronavirus network was basically flat when comparing January 22 and March 4. (2) Spatially, first, from the perspective of regional differences, the network attention in the eastern and central regions decreased in turn. The network users in the eastern region exhibited the highest attention to the new coronavirus, especially in Guangdong, Shandong, Jiangsu and other provinces and cities. The network attention in Tibet, Xinjiang, Qinghai and Ningxia in the western region was the lowest in terms of the national network attention. Second, from the perspective of interprovincial differences, the attention in the new coronavirus network was highly consistent with the Hu Huanyong line of China’s population boundary. The east of the Hu Huanyong line is densely populated, and the network showed high concern, mostly ranking at the third to fifth levels. (3) The number of Internet users in the information technology field, the population, and the culture and age characteristics of individuals are important factors that influence the novel coronavirus attention network. Public Library of Science 2021-09-16 /pmc/articles/PMC8445458/ /pubmed/34529727 http://dx.doi.org/10.1371/journal.pone.0257291 Text en © 2021 Guo et al 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 author and source are credited.
spellingShingle Research Article
Guo, Xiaojia
Zhang, Jing
Wu, Xueling
Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
title Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
title_full Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
title_fullStr Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
title_full_unstemmed Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
title_short Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China
title_sort spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445458/
https://www.ncbi.nlm.nih.gov/pubmed/34529727
http://dx.doi.org/10.1371/journal.pone.0257291
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