Hoax News Detection in Twitter - Kesarkar, Gauri; Babar, Sapana; Aurade, Priyanka; Jaswal, Shree (International Journal of Recent Advances in Multidisciplinary Topics, 2021)
Twitter is one of the online media that is as of now prominently used throughout the world. It’s simply that Twitter has a few issues that unfavorably influence its clients. The lie is one of the negative things that frequently happen in web-based media, news in deception is as yet questioned reality or the reality. In this last project, we created a system to detect COVID-related hoax news on Twitter. Our proposed framework will recognize the fake news based on the given dataset. This project will be worked by performing two machine learning algorithms which are Random Forest and Support Vector Machines. The Twitter dataset will be used as an input to this Machine Learning Model. The correlation will be done on the information prepared by RFC and SVM. It will check for the accuracy of the model by assessing the dataset and perform grouping of information also. The model with the highest accuracy will be utilized for the outcome and discovery of fake news.
Keywords: COVID-19; fake news detection; twitter fake news; hoax news; fake news detection on social media