Fake News Detection: A Brief Investigation Into the State-of-The-Art Approaches and A Mixed Language Dataset

In the era where massive information can be spread easily through social media, fake news detention is increasingly used to prevent widespread misinformation. Machine learning algorithms have been used to identify patterns in news content, and databases are built to filter the false information. This paper investigates the state-of-the-art development into this research domain. A brief review is presented, from public domain dataset to various machine learning models. In addition, a mixed language dataset is presented for future researchers and investigators in this area.