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dc.contributor.authorKong, Jeffery Tzer Huei
dc.contributor.supervisorWei Kitt Wongen_US
dc.contributor.supervisorIk Ying Nguen_US

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 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.

dc.publisherCurtin Universityen_US
dc.titleA multilingual fake news detection on COVID-19 Infodemic in Malaysia using language-independent (Lang-IND) featuresen_US
curtin.departmentCurtin Malaysiaen_US
curtin.accessStatusFulltext not availableen_US
curtin.facultyCurtin Malaysiaen_US
curtin.contributor.orcidKong, Jeffery Tzer Huei [0000-0001-7453-5532]en_US

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