An Application of Machine Learning Models in Detecting Vietnamese Fake News

Nowadays, with the development of the Internet, publishing and sharing news has become very easy, and anyone can do it. Along with the increasing amount of information on the internet, besides official information, fake news continues to rise and spreads quickly across the network. Fake news has become a major societal problem, negatively impacting all aspects of economic, cultural, and social life. How to prevent the spread of fake news online is an urgent issue today. To help readers recognize whether news is trustworthy, this paper proposes using natural language processing techniques and machine learning models to detect fake news in posts on the social network Facebook in the Vietnamese language. After the training process, the resulting model can predict whether the news is real or fake. The model's evaluation results are presented according to popular machine learning metrics, and the best-performing model on the dataset used in this paper is the Light Gradient Boosting Algorithm – LGBM – with an accuracy of 88.21% compared to other models used in this paper.