O uso de data augmentation como técnica para o aprimoramento de redes neurais a fim de detectar notícias falsas sobre a COVID-19

Abstract

This paper aims to present how the application of Natural Lan- guage Processing (NLP) and data augmentation techniques can improve

the performance of a neural network for better detection of fake news in the Portuguese language. Fake news is one of the main controversies during the growth of the internet in the last decade. Verifying what is fact and what is false has proven to be a difficult task, while the dissemination of false news is much faster, which leads to the need for the creation of tools that, automated, assist in the process of verification of what is fact and what is false. In order to bring a solution, an experiment was developed with neural network using news, real and fake, which were never seen by artificial intelligence (AI). There was a significant performance in the news classification after the application of the mentioned techniques.