| 1 | Trump | 4.3% | |
| 2 | Lee | 3.23% | |
| 3 | Korea’s | 3.23% | |
| 4 | North | 3.23% | |
| 5 | China’s | 3.23% | |
| 6 | Indonesia | 2.15% | |
| 7 | Korea | 2.15% | |
| 8 | Europe | 2.15% | |
| 9 | India | 2.15% | |
| 10 | Russia | 2.15% | |
| 11 | Xi | 2.15% | |
| 12 | China | 2.15% | |
| 13 | Ukraine’s | 2.15% | |
| 14 | US | 2.15% | |
| 15 | Jae-myung | 2.15% | |
| 16 | South | 2.15% | |
| 17 | Trump’s | 2.15% | |
| 18 | Friday | 1.08% | |
| 19 | Trees | 1.08% | |
| 20 | Chinas | 1.08% | |
| 21 | New | 1.08% | |
| 22 | Trade | 1.08% | |
| 23 | ‘Godfather | 1.08% | |
| 24 | Japan’s | 1.08% | |
| 25 | PM | 1.08% | |
| 26 | F-15EX | 1.08% | |
| 27 | Dwindling | 1.08% | |
| 28 | Danantara | 1.08% | |
| 29 | Korea? | 1.08% | |
| 30 | Middle | 1.08% | |
| 31 | Ancient | 1.08% | |
| 32 | Trojan | 1.08% | |
| 33 | Wild | 1.08% | |
| 34 | Mecca | 1.08% | |
| 35 | Ground | 1.08% | |
| 36 | Kong | 1.08% | |
| 37 | Thailand | 1.08% | |
| 38 | Ispace | 1.08% | |
| 39 | Bengaluru | 1.08% | |
| 40 | Hong | 1.08% | |
| 41 | Will | 1.08% | |
| 42 | TikTok | 1.08% | |
| 43 | Koreans | 1.08% | |
| 44 | Malaysia | 1.08% | |
| 45 | J-10 | 1.08% | |
| 46 | Imprisoned | 1.08% | |
| 47 | Tiananmen | 1.08% | |
| 48 | Zealand | 1.08% | |
| 49 | Wong | 1.08% | |
| 50 | Moon | 1.08% | |
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는 분류, 데이터 기준으로 의 기사에서 의 고유명사 데이터를 통해 생성되었습니다.
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