| 1 | Trump | 3.6% | |
| 2 | Korea’s | 2.7% | |
| 3 | Lee | 2.7% | |
| 4 | Russia | 2.7% | |
| 5 | North | 2.7% | |
| 6 | Ukraine’s | 2.7% | |
| 7 | Trump’s | 2.7% | |
| 8 | China’s | 2.7% | |
| 9 | Xi | 1.8% | |
| 10 | Korea | 1.8% | |
| 11 | India | 1.8% | |
| 12 | Indonesia | 1.8% | |
| 13 | Europe | 1.8% | |
| 14 | Will | 1.8% | |
| 15 | China | 1.8% | |
| 16 | Jae-myung | 1.8% | |
| 17 | US | 1.8% | |
| 18 | South | 1.8% | |
| 19 | Ukraine | 1.8% | |
| 20 | Friday | 0.9% | |
| 21 | Trees | 0.9% | |
| 22 | Chinas | 0.9% | |
| 23 | New | 0.9% | |
| 24 | Golden | 0.9% | |
| 25 | Trade | 0.9% | |
| 26 | ‘Godfather | 0.9% | |
| 27 | Japan’s | 0.9% | |
| 28 | PM | 0.9% | |
| 29 | F-15EX | 0.9% | |
| 30 | Dwindling | 0.9% | |
| 31 | Danantara | 0.9% | |
| 32 | Korea? | 0.9% | |
| 33 | Dome | 0.9% | |
| 34 | Li | 0.9% | |
| 35 | Middle | 0.9% | |
| 36 | Ancient | 0.9% | |
| 37 | Trojan | 0.9% | |
| 38 | Wild | 0.9% | |
| 39 | Pacific’s | 0.9% | |
| 40 | Mecca | 0.9% | |
| 41 | Ground | 0.9% | |
| 42 | Kong | 0.9% | |
| 43 | Air | 0.9% | |
| 44 | Thailand | 0.9% | |
| 45 | Ispace | 0.9% | |
| 46 | Bengaluru | 0.9% | |
| 47 | Tibetans | 0.9% | |
| 48 | Hong | 0.9% | |
| 49 | US-China | 0.9% | |
| 50 | VietJet | 0.9% | |
|
는 분류, 데이터 기준으로 의 기사에서 의 고유명사 데이터를 통해 생성되었습니다.
|
|||