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    A multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) features

    Kong JTH 2023 Public 2years.pdf (1.405Mb)
    Access Status
    Open access
    Authors
    Kong, Jeffery Tzer Huei
    Date
    2023
    Supervisor
    Wei Kitt Wong
    Ik Ying Ngu
    Type
    Thesis
    Award
    MPhil
    
    Metadata
    Show full item record
    Faculty
    Curtin Malaysia
    School
    Curtin Malaysia
    URI
    http://hdl.handle.net/20.500.11937/92188
    Collection
    • Curtin Theses
    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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