Fast Naïve Bayes classifiers for COVID-19 news in social networks
Hasan Dwi Cahyono,
Atara Mahadewa,
Ardhi Wijayanto
et al.
Abstract:The growth of fake news has emerged as a substantial societal concern, particularly in the context of the COVID-19 pandemic. Fake news can lead to unwarranted panic, misinformed decisions, and a general state of confusion among the public. Existing methods to detect and filter out fake news have accuracy, speed, and data distribution limitations. This study explores a fast and reliable approach based on Naïve Bayes algorithms for fake news detection on COVID-19 news in social networks. The study used a dataset… Show more
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