Bilingual Fake News Detection Algorithm Using Naïve Bayes and Support Vector Machine Models

This study aims to mitigate the absorption of fraudulent news by exploring the feasibility of using Naive Bayes and SGD classifier models in predicting whether the English or Filipino article is real or fake. This is accomplished by training the models through large pre-processed datasets. After evaluation, both models have achieved an accuracy of 93% and 95% accuracy respectively.