Table 3. Frequency analysis of AI policies by government type
| Ranking | Central government | Eastern local government |
| Keyword | TF-IDF | Keyword | TF-IDF |
| 1 | Earthquake | 0.931 | Region | 0.839 |
| 2 | Situation | 0.902 | Limited_Company | 0.797 |
| 3 | School | 0.886 | Smart | 0.747 |
| 4 | Headquarters | 0.865 | This_City | 0.736 |
| 5 | Fund | 0.859 | Industry | 0.711 |
| 6 | Member | 0.825 | Curriculum | 0.679 |
| 7 | Experimental_Zone | 0.745 | Academic_Society | 0.678 |
| 8 | Teacher | 0.744 | Major | 0.660 |
| 9 | Provision | 0.720 | Medical_Institution | 0.656 |
| 10 | Medical_Equipment | 0.719 | Model | 0.643 |
| Ranking | Central local government | Western local government | |
| Keyword | TF-IDF | Keyword | TF-IDF |
| 1 | Scientific_Technology | 1.000 | Pandemic | 0.722 |
| 2 | Norm | 0.811 | Project | 0.656 |
| 3 | Smart | 0.776 | Data | 0.649 |
| 4 | Professional | 0.755 | Expert | 0.632 |
| 5 | Enterprise | 0.642 | Entire_City | 0.621 |
| 6 | Pandemic | 0.614 | Norm | 0.618 |
| 7 | Email | 0.581 | Autonomous_District | 0.572 |
| 8 | Voice | 0.491 | Smart | 0.554 |
| 9 | Standard | 0.484 | Industry | 0.549 |
| 10 | Committee | 0.454 | Consultation_Hotline | 0.532 |
AI, artificial intelligence; TF-IDF, term frequency-inverse document frequency.