Neural Network based Fake News Detection using NLP Technique

Although social media platforms let us consume news much more quickly and allow for less controlled editing, fake news is spreading incredible pace and faster. The world has been greatly impacted by fake news since it aims to impact crowd opinion and impact decisions in a specific direction. The work and cost of manually confirming the legitimacy of news have attracted a lot of interest from researchers. Therefore this paper presents, Neural network based Fake News detection using NLP technique. The suggested method is predicated on a Romanian news corpus that includes 13,064 fake and 25,841 real news items. NLP, or Natural language processing, is utilized in the data preparation process. In this study uses the Domain Adversarial Neural Network (DANN) model for the detection of fake news. According to experimental data, the suggested model outperforms other deep learning models in terms of Precision, F1-Score, Recall and Accuracy. By effectively identifying fake news, the negative impact of fake news on communities can be reduced by these achievements.