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COVID-19 news classification using cosine similarity algorithm |
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| รหัสดีโอไอ | |
| Creator | Aukkritthiwat Phimpha |
| Title | COVID-19 news classification using cosine similarity algorithm |
| Contributor | Suthida Chaichomchuen, Vatinee Nuipian |
| Publisher | Mahasarakham University |
| Publication Year | 2569 |
| Journal Title | Journal of Science and Technology Mahasarakham University |
| Journal Vol. | 45 |
| Journal No. | 4 |
| Page no. | 437-445 |
| Keyword | Text classification, text mining, cosine similarity, COVID-19 |
| URL Website | https://li01.tci-thaijo.org/index.php/scimsujournal |
| Website title | Journal of Science and Technology Mahasarakham University |
| ISSN | 1686-9664 (Print), 2586-9795(Online) |
| Abstract | The research addresses how the pandemic created a flood of diverse and unregulated content about outbreak management. Using cosine similarity analysis on news from Khaosod, Matichon, and MCOT websites, researchers developed a classification system achieving an accuracy of up to 82.50%. |
