Research Article
Analyzing the Spatio-Temporal Characteristics and Influencing Factors of “AI + Education” Network Attention in China
Table 2
G and Gini of “AI + Education” network attention.
| Year | Geographic concentration index (G) | Provincial level (Gini) | Regional level (Gini) | Eastern | Central | Western |
| 2012 | 0.1944 | 0.4146 | 0.3110 | 0.1919 | 0.3878 | 2013 | 0.1924 | 0.3835 | 0.2967 | 0.1756 | 0.3843 | 2014 | 0.1928 | 0.3907 | 0.3018 | 0.1729 | 0.3757 | 2015 | 0.1938 | 0.4052 | 0.3282 | 0.1701 | 0.3965 | 2016 | 0.1992 | 0.4750 | 0.3927 | 0.1796 | 0.4805 | 2017 | 0.2122 | 0.6296 | 0.5382 | 0.2617 | 0.4982 | 2018 | 0.2088 | 0.5924 | 0.5208 | 0.2765 | 0.4800 | 2019 | 0.2038 | 0.5362 | 0.4933 | 0.2283 | 0.4395 | 2020 | 0.1996 | 0.4843 | 0.4520 | 0.2033 | 0.4482 |
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