A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features
Access Status
Open access
Date
2023Supervisor
Wei Kitt Wong
Ik Ying Ngu
Type
Thesis
Award
MPhil
Metadata
Show full item recordFaculty
Curtin Malaysia
School
Curtin Malaysia
Collection
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.
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