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Fig 1.

Research design for the spatiotemporal dynamics of public attention.

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Fig 1 Expand

Fig 2.

Time series characteristics of the public attention index in China.

(a) The monthly average public attention index in China, 2019–2013. (b) The seasonal index of public attention index from January to December.

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Fig 2 Expand

Table 1.

Seasonal concentration index and Herfindahl index of public attention index in China.

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Table 1 Expand

Fig 3.

Average daily public attention index of 363 cities in China.

Subfigures (a) to (e) depict the average daily PAI for 363 cities from 2019 to 2023, respectively. Note: Fig 3 was produced based on the standard map GS (2019) 1822 on the website of the Standard Map Service of the Ministry of Natural Resources of China, with no modifications to the boundaries of the base map.

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Fig 3 Expand

Table 2.

Spatial autocorrelation results for the public attention index in China.

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Table 2 Expand

Fig 4.

The cluster and outlier analysis of the average daily public attention index.

Subfigures (a) to (e) depict the cluster and outlier analysis results from 2019 to 2023, respectively. Note: Fig 4 was produced based on the standard map GS (2019) 1822 on the website of the Standard Map Service of the Ministry of Natural Resources of China, with no modifications to the boundaries of the base map.

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Fig 4 Expand

Fig 5.

Tendency of the intra-regional Gini coefficient of public attention.

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Fig 5 Expand

Fig 6.

Tendency of the inter-regional Gini coefficient of public attention.

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Fig 7.

The sources of the differences in public attention and the trends of their contributions.

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Fig 7 Expand