A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features
dc.contributor.author | Kong, Jeffery Tzer Huei | |
dc.contributor.supervisor | Wei Kitt Wong | en_US |
dc.contributor.supervisor | Ik Ying Ngu | en_US |
dc.date.accessioned | 2023-05-23T03:37:52Z | |
dc.date.available | 2023-05-23T03:37:52Z | |
dc.date.issued | 2023 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/92188 | |
dc.description.abstract |
The study proposed a fake news detection model using Lang-IND features by implementing a two-stage evolutionary approach to generate and optimize the best mathematical equation to detect fake news. Results from the first stage shows that the equation from GP scores F1-score of 83.23% on Fake.my-COVID19 dataset. After fine-tuning stage, the model performance increases the F1-score to 85.52%. The proposed two-stage evolutionary approach performance result is higher as compared to the traditional machine learning algorithms. | en_US |
dc.publisher | Curtin University | en_US |
dc.title | A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | MPhil | en_US |
curtin.department | Curtin Malaysia | en_US |
curtin.accessStatus | Fulltext not available | en_US |
curtin.faculty | Curtin Malaysia | en_US |
curtin.contributor.orcid | Kong, Jeffery Tzer Huei [0000-0001-7453-5532] | en_US |
dc.date.embargoEnd | 2025-05-22 |