COVID-19 Fake News Detection with Deep Learning

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dc.contributor.authorKowirat, Rutchaneewan
dc.contributor.authorBoongasame, Laor
dc.date.accessioned2026-08-06T10:39:58Z
dc.date.available2026-08-06T10:39:58Z
dc.date.issued2023-01-01
dc.description.abstractSocial media has become one of the most popular channels to keep updated with daily news because it can quickly and easily access information. This advantage is used by malicious people to spread fake news widely. Since the COVID-19 pandemic, fake news has become a huge social problem, causing people to panic and misunderstand how to cure or protect themselves from the virus. So, the goal of this research is to use deep learning as the Recurrent Neural Network (RNN) model to find fake news about COVID-19 in the Thai language on social media and help filter information by classifying real and fake news.
dc.identifier.citationAsia Pacific Journal of Information Systems, 33(1), 69-82, 2023
dc.identifier.doi10.14329/apjis.2023.33.1.69
dc.identifier.issn22885404
dc.identifier.other2-s2.0-85163057433
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/14008
dc.sourceAsia Pacific Journal of Information Systems
dc.subjectCOVID-19
dc.subjectDeep Learning
dc.subjectFake News
dc.subjectRecurrent Neural Network (RNN) Model
dc.subjectSocial Media
dc.titleCOVID-19 Fake News Detection with Deep Learning
dc.typeArticle

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