Comparison of CNN Model with Different Machine Learning Models for Fake News Detection

Fake news continues to be a critical issue in today's era for any citizen concerned about political integrity and the state of governance. The use of internet has experienced exponential growth, leading to an increase in fake news or misinformation. This misinformation negatively impacts individuals and societies. Therefore, It is critical to stop and identify fake news. In this paper, we develop a model based on convolutional neural networks for detecting fake news. We also compare our proposed model with eight other machine learning models using various metrics. Our model achieved an accuracy of 98.52%, outperforming all other models, with support vector machine (SVM) proving to be the best among the machine learning models used.