Detection of Fake News Using Machine Learning (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
The easy access and exponential growth of the knowledge available on social media networks has made it intricate to differentiate between false and true information. The easy dissemination of data by way of sharing has added to exponential extension of its falsification. The reliability of social media networks is also at stake where spreading of fake information is pervasive. Thus, it has become a research challenge to automatically check the information viz a viz it’s source, content and the publisher for categorizing it as true or false. Machine learning has played an important role within the classification of data although with some limitations. This paper reviews various Machine learning approaches in the detection of fabricated and fake news. The limitation of such approaches and improvisation by way of the implementing deep learning is also reviewed.