A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features
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-COVI...
| Main Author: | |
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| Format: | Thesis |
| Published: |
Curtin University
2023
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| Online Access: | http://hdl.handle.net/20.500.11937/92188 |
| _version_ | 1848765622980182016 |
|---|---|
| author | Kong, Jeffery Tzer Huei |
| author_facet | Kong, Jeffery Tzer Huei |
| author_sort | Kong, Jeffery Tzer Huei |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:38:11Z |
| format | Thesis |
| id | curtin-20.500.11937-92188 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:38:11Z |
| publishDate | 2023 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-921882025-06-16T03:26:30Z A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features Kong, Jeffery Tzer Huei 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. 2023 Thesis http://hdl.handle.net/20.500.11937/92188 Curtin University fulltext |
| spellingShingle | Kong, Jeffery Tzer Huei A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features |
| title | A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features |
| title_full | A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features |
| title_fullStr | A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features |
| title_full_unstemmed | A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features |
| title_short | A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features |
| title_sort | multilingual fake news detection on covid-19 infodemic in malaysia using language-independent (lang-ind) features |
| url | http://hdl.handle.net/20.500.11937/92188 |