Spotting misinformation to limit the impact of disruption on society by using machine learning

Deceptive information attracts most and it creates most dangerous impact on society. As we know, fighting against pandemic is as dangerous as fighting against infodemic, so we have to find a solution to limit the impact of disruption on society. To win the battle, first we need to spot misinformation and in this case machine learning gives us a stunning result. To put a stop to the spread of viral deceptive information, it is important to identify them first. In this paper, after introducing the dataset, various operations are done, where natural language processing (NLP) plays an important role. Here, machine learning algorithm recurrent neural network (RNN), convolutional neural network (CNN), support vector machine (SVM), naïve Bayes are used to spot misinformation. In this paper, the future research direction, the challenges are also mentioned. To overcome such problems the predicted solution is also discussed.