ArticlePloS one2021
Spatio-temporal characteristics of the novel coronavirus attention network and its influencing factors in China.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Analysis of the temporal and spatial evolution of China's air passenger transportation and the impact of policies on passenger flows.PloS one · 2025Article
- Spatiotemporal characteristics and influencing factors of network attention to resort hotels in China.Heliyon · 2024Article
- Article
- Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China.PloS one · 2024Article
- Seeing the forest and the trees: Holistic view of social distancing on the spread of COVID-19 in China.Applied geography (Sevenoaks, England) · 2023Article
- Article
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3 authors.
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Abstract
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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