Fake News Detection on Social Media: Case Study of 2019 Novel Coronavirus - Rutchaneewan Kowirat; Laor Boongasame (My University, 2021)
Fake news is news that is created with the intent to deceive and mislead readers. It is a problem that occurs in every era because it creates misunderstandings for people through a variety of media channels such as newspapers, radio, or television. Nowadays, fake news has become a big problem. When social media has become another channel to increase the spread of fake news and came to play a big role during the epidemic like COVID-19. Fake news creates panic and creates false knowledge of how to protect yourself from COVID-19. Therefore, the objective of this research is to create a method that can detect fake news on social media. It focuses only on news related to COVID-19. In addition, the information was extracted directly from social media such as Twitter. Moreover, this research applying machine learning processes to classify real and fake news. From the experimental results, the accuracy was measured at 99.92% with the Decision Tree model.
Keywords: Misinformation and Its Impacts; Sentiment Analysis and Opinion Mining; Spam and Phishing Detection