Figure 1:
Spatial distribution of China’s 5A-level tourist attractions
Table 1:
Statistical analysis of Douyin accounts for China’s 5A-level tourist attractions
| provincial-level administrative division | the number of 5A-level tourist attractions | the number of official Douyin accounts for tourist attractions | the number of accounts with a fan base exceeding 10,000 | in total |
|---|---|---|---|---|
| Beijing | 8 | 8 | 26 | 34 |
| Tianjin | 2 | 1 | 2 | 3 |
| Hebei | 11 | 7 | 81 | 88 |
| Shanxi | 10 | 9 | 98 | 107 |
| Inner Mongolia | 6 | 3 | 5 | 8 |
| Liaoning | 6 | 9 | 2 | 11 |
| Jilin | 7 | 12 | 13 | 25 |
| Heilongjiang | 6 | 8 | 3 | 11 |
| Shanghai | 4 | 7 | 2 | 9 |
| Jiangsu | 25 | 51 | 11 | 62 |
| Zhejiang | 20 | 30 | 143 | 173 |
| Anhui | 12 | 20 | 46 | 66 |
| Fujian | 10 | 17 | 27 | 44 |
| Jiangxi | 14 | 41 | 52 | 93 |
| Shandong | 14 | 22 | 32 | 54 |
| Henan | 15 | 33 | 43 | 76 |
| Hubei | 14 | 25 | 44 | 69 |
| Hunan | 11 | 18 | 67 | 85 |
| Guangdong | 15 | 24 | 17 | 41 |
| Guangxi | 9 | 12 | 9 | 21 |
| Hainan | 6 | 7 | 11 | 18 |
| Chongqing | 11 | 15 | 2 | 17 |
| Sichuan | 16 | 24 | 32 | 56 |
| Guizhou | 9 | 17 | 10 | 27 |
| Yunnan | 9 | 13 | 24 | 37 |
| Tibet | 5 | 8 | 1 | 9 |
| Shaanxi | 12 | 36 | 42 | 78 |
| Gansu | 7 | 11 | 3 | 14 |
| Qinghai | 4 | 4 | 0 | 4 |
| Ningxia | 4 | 4 | 1 | 5 |
| Xinjiang | 17 | 29 | 20 | 49 |
| in total | 318 | 525 | 869 | 1394 |
Figure 2:
Data retrieval route
Figure 3:
Rank-size distribution of network attention to Douyin’s fans
Figure 4:
Spatial pattern of fan quantity and attention level on Douyin
Figure 5:
Density analysis of Douyin’s fans for China’s 5A-level tourist attractions
Note: The map is drawn based on the standard map of the Ministry of Natural Resources of China (Map Approval Number GS(2019)1822), and the base map remains unmodified. Data for Hong Kong, Macau, and Taiwan are not available.
Table 2:
Douyin’s fans and attention levels of China’s 5A-level tourist attractions attractions
| level | the number of fans (ten thousand) | the number of scenic spots | proportion (%) |
|---|---|---|---|
| low attention | 0.000000–33.000000 | 246 | 77.4 |
| lower attention | 33.000001–113.400000 | 45 | 14.2 |
| moderate attention | 113.400001–273.400000 | 14 | 4.4 |
| higher attention | 273.400001–645.800000 | 11 | 3.5 |
| high attention | 645.800001–1983.500000 | 2 | 0.6 |
Table 3:
Analysis of proximity and aggregation of scenic spots
| level of attention | the number of scenic spots | ANN | Z | P | distribution types |
|---|---|---|---|---|---|
| low attention | 246 | 0.684190 | −9.475993 | 0.000000 | significant aggregation |
| lower attention | 45 | 0.990576 | −0.119584 | 0.904813 | low aggregation |
| moderate attention | 14 | 1.030877 | 0.243555 | 0.807576 | random distribution |
| higher and high attention | 13 | 1.215827 | 1.488704 | 0.136565 | random distribution |
Table 4:
Construction of indicator system for influencing factors
| primary indicators | secondary indicators | explanation of indicators |
|---|---|---|
| the marketing market of tourist attractions (A1) | ticket price | original price of the scenic spot ticket |
| construction of scenic spot | the number of Douyin | the number of Douyin |
| promotion platform (A2) | accounts | accounts |
| the level of regional economic development (A3) | regional GDP | overall level of regional economy |
| the support of modern service industry (A4) | the proportion of value added in the tertiary industry | the support for the development of scenic spots |
| the level of internet development (A5) | the number of fixed broadband internet access users | the level of regional network development |
| transportation accessibility (A6) | passenger turnover | level of regional transportation development |
| regional population carrying capacity (A7) | population size of the region | population size in the region |
| the vibrant development of the tourism market (A8) | tourism revenue | the economic strength of scenic spots |
Table 5:
Regression analysis of influencing factors
| A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | |
|---|---|---|---|---|---|---|---|---|
| q | 0.09568 | 0.56652 | 0.05124 | 0.01603 | 0.01211 | 0.01869 | 0.01862 | 0.02151 |
| 5 | 9 | 6 | 2 | 4 | 6 | 3 | ||
| p | 0.000 | 0.000 | 0.00481 | 0.29020 | 0.43529 | 0.20915 | 0.21865 | 0.15053 |
| 6 | 4 | 7 | 2 |
Table 6:
Results of influencing factors to interaction detection
| A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | ||
|---|---|---|---|---|---|---|---|---|---|
| A1 | 0.095685 | - | - | - | - | - | - | - | |
| A2 | 0.642814 | 0.56652 | - | - | - | - | - | - | |
| 9 | |||||||||
| q | A3 | 0.305793 | 0.88347 | 0.0512 | - | - | - | - | - |
| 8 | 46 | ||||||||
| A4 | 0.168963 | 0.64695 | 0.0915 | 0.01603 | - | - | - | - | |
| 5 | 2 | 2 | |||||||
| A5 | 0.154204 | 0.88084 | 0.0589 | 0.03032 | 0.0121 | - | - | - | |
| 8 | 77 | 5 | 14 | ||||||
| A6 | 0.174978 | 0.73640 | 0.0572 | 0.08503 | 0.0600 | 0.01869 | - | - | |
| 9 | 16 | 7 | 38 | ||||||
| A7 | 0.239621 | 0.87910 | 0.0937 | 0.06834 | 0.0822 | 0.05143 | 0.01862 | - | |
| 9 | 41 | 6 | 78 | 2 | 6 | ||||
| A8 | 0.188124 | 0.60222 | 0.0887 | 0.04575 | 0.0504 | 0.04647 | 0.04350 | 0.0215 | |
| 4 | 01 | 82 | 3 | 2 | 13 | ||||
| result | A1 | - | - | - | - | - | - | - | - |
| A2 | ◎ | - | - | - | - | - | - | - | |
| A3 | ○ | ○ | - | - | - | - | - | - | |
| A4 | ○ | ○ | ○ | - | - | - | - | - | |
| A5 | ○ | ○ | ◎ | ◎ | - | - | - | - | |
| A6 | ○ | ○ | ◎ | ○ | ○ | - | - | - | |
| A7 | ○ | ○ | ○ | ○ | ○ | ○ | - | - | |
| A8 | ○ | ○ | ○ | ○ | ○ | ○ | ◎ | - |