A Study of Fake News Detection Using Machine Learning Techniques

The number of people using the Internet has significantly expanded due to the advancement of information and communication technology. It converts people's conventional news and information consumption habits into online ones, benefiting news broadcasters and readers by enabling comfort, speed. These days, massive false reports (news) are constantly uploaded by hostile clients with deceitful objectives, prompting calamitous social consequences for people and society and making ceaseless dangers a majority rule government, equity, and public trust. It is especially significant in online entertainment stages (e.g., Snapchat, Twitter, Facebook) because to their inherent, unrestrained publishing methods and platforms. Same issues have determined the work of the academic world as well as enterprises for growing more precise fake news recognition. In this paper, different machine learning methods are introduced, which are implemented in other datasets to observe which method is most efficient in this field.