FAKE NEWS DETECTION USING MACHINE LEARNING ALGORITHMS- A REVIEW

The increasing spread of fake news poses a serious threat to the credibility of information sources and public discourse. Machine learning algorithms have been increasingly used to identify fake news and differentiate them from real news. In this project, we propose to develop a fake news detection system using machine learning algorithms. The proposed system will use a dataset of news articles labelled as real or fake and will leverage natural language processing (NLP) techniques to extract features and train a machine learning model. The model will be evaluated using standard metrics such as accuracy, precision, recall, and F1 score. The results of this project could help to mitigate the impact of fake news on society and enable more informed decision-making.