Design of a Robust Technique for Fake News Detection

In this digital era, where we are connected to everyone through the Internet and various social media platforms, we require authentic knowledge, data and information sources. But it is very hard to find or detect it easily. However, there are multiple tools available to detect such trustworthiness. However, they lack the proper detection of fake news. Hence sometimes, the detection does not happen up to a satisfactory level. In this paper, we propose a scheme for the detection of fake news. We use the machine learning models with the most recent data set available at authentic source. Further, the performance of the proposed technique is estimated under various machine learning models, i.e., naive bayes classifier, logistic regression, and support vector machine (SVM). The proposed technique has performed well under the support vector machine, achieving the highest accuracy value under this model.